Data generation method and device, computer device, and storage medium

Abstract

The embodiment of the application belongs to the field of big data, and relates to a data generation method, comprising the following steps: receiving a sampling data generation task triggered by a user; displaying a sampling information configuration page, and receiving sampling configuration information input by the user on the sampling information configuration page; determining a task processing time based on a sampling type, and when the current time reaches the task processing time, calling a sampling engine, querying a preset database based on a task name to obtain initial data; generating a first sampling condition based on a sampling strategy, a product name and a business name; performing preset processing on the first sampling condition based on a sampling quantity type to obtain a second sampling condition; and performing data filtering processing on the initial data based on the sampling strategy condition and the second sampling condition to obtain target data. The application also provides a data generation device, a computer device and a storage medium. In addition, the application also relates to blockchain technology, and the target data can be stored in the blockchain. The application improves the generation efficiency of the target data.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to data generation methods, devices, computer equipment and storage media. Background Art

[0002] In today's society, more and more people are beginning to attach importance to purchasing insurance. As the number of insurance purchases continues to increase, the number of claims applications is also increasing, and the workload of reviewing whether there are any abnormal data in claims cases is also increasing. In existing technologies, reviewers need to manually search for suspected data that needs to be sampled from the claims cases in the claims system. They then review this suspected data based on historical preservation records, underwriting records, and the reasons for the claim. However, the number of suspected data in claims cases is often large, and manually searching for data that needs to be sampled consumes a lot of manpower and material resources, is inefficient, and lacks intelligence. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to propose a data generation method, device, computer equipment and storage medium to solve the technical problems that the existing method of manually searching for data that needs to be sampled requires a lot of manpower and material resources, has low processing efficiency and lacks intelligence.

[0004] In order to solve the above technical problems, the present application provides a data generation method, which adopts the following technical solutions:

[0005] Receive user-triggered sampling data generation tasks;

[0006] Displaying a preset sampling information configuration page and receiving the sampling configuration information input by the user on the sampling information configuration page; wherein the sampling configuration information includes basic configuration information and sampling strategy conditions, wherein the basic configuration information includes at least the task name, sampling strategy, sampling type, and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and business name;

[0007] Determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine, and query a preset database based on the task name to obtain corresponding initial data;

[0008] Generate a first sampling condition based on the sampling strategy, the product name, and the business name;

[0009] Based on the sampling quantity type, presetting the first sampling condition to obtain a second sampling condition;

[0010] Filter the initial data based on the sampling strategy condition and the second sampling condition to obtain target data to be sampled.

[0011] Further, the step of generating the first sampling condition based on the sampling strategy, the product name, and the business name specifically includes:

[0012] Obtaining a corresponding business interface based on the product name and the business name;

[0013] If the sampling strategy is a first preset sampling strategy, dividing the business interface into a first number of first business interface sets according to preset priority level information, and storing the first business interface sets in a preset initial sampling condition to obtain the first sampling condition;

[0014] If the sampling strategy is a second preset sampling strategy, dividing the business interface into a second number of second business interface sets according to a preset content type;

[0015] Determining the priority of each second business interface set and determining the data extraction ratio of each second business interface set based on the priority of each second business interface set;

[0016] Storing the second business interface sets and the data extraction ratio in the initial sampling condition to obtain the first sampling condition.

[0017] Further, the step of determining the data extraction ratio of each second business interface set based on the priority of each second business interface set specifically includes:

[0018] Determining a priority value of each second business interface set based on the priority of each second business interface set;

[0019] Calculating the sum of all priority values;

[0020] Calculating the quotient value of a specified priority value and the sum; wherein the specified priority value is a priority value of any second business interface set;

[0021] Taking the quotient value as the data extraction ratio of the second business interface set corresponding to the specified priority value.

[0022] Further, the step of performing preset processing on the first sampling condition to obtain the second sampling condition based on the sampling amount type specifically includes:

[0023] Determining whether the sampling amount type is unlimited;

[0024] If the sampling quantity type is unlimited, the value of the preset first variable is set to 0, and the first variable is stored in the first sampling condition to obtain the second sampling condition;

[0025] If the sampling quantity type is not unlimited, determine whether the sampling quantity type is percentage;

[0026] If the sampling quantity type is a percentage, the value of the first variable is set to 1, and the percentage value corresponding to the sampling quantity type is assigned to the preset second variable;

[0027] The first variable and the second variable are stored in the first sampling inspection condition to obtain the second sampling inspection condition.

[0028] Furthermore, the step of performing data filtering processing on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain the target data to be sampled specifically includes:

[0029] Obtain the business interface set within the second sampling condition;

[0030] Determining whether the service interface set includes the first service interface set;

[0031] If the first service interface set is included, based on the sampling policy conditions and the preset sorting order, filtering the initial data to obtain first data, and storing the first data in a preset storage unit;

[0032] Obtaining the value of the first variable within the second sampling condition;

[0033] If the value of the first variable in the second sampling condition is 0, all the first data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled;

[0034] If the value of the first variable in the second sampling condition is 1, obtain the value of the second variable in the second sampling condition;

[0035] performing data extraction processing on all the first data in the storage unit based on the value of the second variable to obtain second data;

[0036] The second data is stored in the target data table of the database to obtain the target data.

[0037] Furthermore, after the step of determining whether the service interface set includes the first service interface set, the method further includes:

[0038] If the first service interface set is not included, determining whether the service interface set includes the second service interface set;

[0039] If the second service interface set is included, performing data filtering processing on the initial data based on the sampling policy condition and the data extraction ratio to obtain third data, and storing the third data in the storage unit;

[0040] Obtaining the value of the first variable within the second sampling condition;

[0041] If the value of the first variable in the second sampling condition is 0, all the third data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled;

[0042] If the value of the first variable in the second sampling condition is 1, obtain the value of the second variable in the second sampling condition;

[0043] performing data extraction processing on all the third data in the storage unit based on the value of the second variable to obtain fourth data;

[0044] The fourth data is stored in the target data table of the database to obtain the target data.

[0045] Furthermore, after the step of performing data filtering processing on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain the target data to be sampled, the method further includes:

[0046] generating a sampling inspection task corresponding to the target data;

[0047] Perform the sampling inspection task;

[0048] Obtaining the task execution result corresponding to the sampling inspection task;

[0049] The task execution results are stored and displayed.

[0050] In order to solve the above technical problems, the embodiment of the present application further provides a data generation device, which adopts the following technical solution:

[0051] A first receiving module is used to receive a sampling data generation task triggered by a user;

[0052] a second receiving module, configured to display a preset sampling inspection information configuration page and receive the sampling inspection configuration information input by the user on the sampling inspection information configuration page; wherein the sampling inspection configuration information includes basic configuration information and sampling inspection strategy conditions, wherein the basic configuration information includes at least the task name, sampling inspection strategy, sampling inspection type, and sampling inspection quantity type of the sampling inspection data generation task, and the sampling inspection strategy conditions include at least the product name and the business name;

[0053] A query module is used to determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine to query a preset database based on the task name to obtain corresponding initial data;

[0054] A first generating module, configured to generate a first sampling condition based on the sampling strategy, the product name, and the business name;

[0055] A first processing module, configured to perform preset processing on the first sampling condition based on the sampling quantity type to obtain a second sampling condition;

[0056] The second processing module is used to perform data filtering processing on the initial data based on the sampling strategy condition and the second sampling condition to obtain target data to be sampled.

[0057] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0058] Receive user-triggered sampling data generation tasks;

[0059] Displaying a preset sampling information configuration page and receiving the sampling configuration information input by the user on the sampling information configuration page; wherein the sampling configuration information includes basic configuration information and sampling strategy conditions, wherein the basic configuration information includes at least the task name, sampling strategy, sampling type, and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and business name;

[0060] Determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine, and query a preset database based on the task name to obtain corresponding initial data;

[0061] Generate a first sampling condition based on the sampling strategy, the product name, and the business name;

[0062] Based on the sampling quantity type, presetting the first sampling condition to obtain a second sampling condition;

[0063] The initial data is filtered based on the sampling inspection strategy condition and the second sampling inspection condition to obtain target data to be sampled.

[0064] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0065] Receive user-triggered sampling data generation tasks;

[0066] Displaying a preset sampling information configuration page and receiving the sampling configuration information input by the user on the sampling information configuration page; wherein the sampling configuration information includes basic configuration information and sampling strategy conditions, wherein the basic configuration information includes at least the task name, sampling strategy, sampling type, and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and business name;

[0067] Determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine, and query a preset database based on the task name to obtain corresponding initial data;

[0068] Generate a first sampling condition based on the sampling strategy, the product name, and the business name;

[0069] Based on the sampling quantity type, presetting the first sampling condition to obtain a second sampling condition;

[0070] The initial data is filtered based on the sampling inspection strategy condition and the second sampling inspection condition to obtain target data to be sampled.

[0071] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0072] After receiving the sampling data generation task triggered by the user, the embodiment of the present application will first display the preset sampling information configuration page, and receive the sampling configuration information entered by the user on the sampling information configuration page, then determine the task processing time based on the sampling type, and when the current time reaches the task processing time, call the preset sampling engine, query the preset database based on the task name to obtain the corresponding initial data, and then generate the first sampling condition based on the sampling strategy, product name and business name, and then perform preset processing on the first sampling condition based on the sampling quantity type to obtain the second sampling condition, and finally perform data filtering processing on the initial data based on the sampling strategy condition and the second sampling condition to obtain the target data to be sampled. By adopting the solution of the present application, the user only needs to enter the sampling configuration information on the page, and the sampling engine can be used to automatically and quickly extract the target data to be sampled from the initial data in the database, effectively improving the generation efficiency and generation intelligence of the target data and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0074] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0075] Figure 2 A flowchart of an embodiment of a data generation method according to the present application;

[0076] Figure 3 is a structural diagram of an embodiment of a data generating device according to the present application;

[0077] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0079] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0080] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0081] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. Network 104 is a medium for providing communication links between terminal devices 101, 102, 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0082] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0083] Terminal devices 101, 102, and 103 can be various electronic devices with display screens and support web browsing, including but not limited to smartphones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV), laptop computers, desktop computers, etc.

[0084] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0085] It should be noted that the data generation method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the data generation device is generally set in the server / terminal device.

[0086] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0087] Continue to refer Figure 2 , shows a flow chart of an embodiment of a data generation method according to the present application. The data generation method comprises the following steps:

[0088] Step S201: receiving a sampling data generation task triggered by a user.

[0089] In this embodiment, the data generation method is executed on the electronic device (eg Figure 1 The content review platform within the server / terminal device shown in the figure can obtain the sampling data generation task through a wired connection or a wireless connection. It should be pointed out that the above-mentioned wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods that are currently known or will be developed in the future. Among them, after logging into the content review platform of the electronic device, the user enters the sampling information configuration page that provides the review and sampling service, and can create a sampling data generation task based on actual conditions. The review and sampling service is divided into two modules: basic configuration information and sampling policy conditions.

[0090] Step S202, display the preset sampling information configuration page, and receive the sampling configuration information entered by the user on the sampling information configuration page; wherein, the sampling configuration information includes basic configuration information and sampling strategy conditions, the basic configuration information includes at least the task name, sampling strategy, sampling type and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and business name.

[0091] In this embodiment, the above-mentioned basic configuration information is composed of four factors: task name, sampling strategy, sampling type, and sampling quantity type. Among them, the above-mentioned task name can be customized by the user. The above-mentioned sampling strategy includes three types: high priority sampling, geometric ratio, and average. The user can select the above three sampling strategies on the sampling information configuration page, and the electronic device can perform sampling processing accordingly according to the sampling strategy selected by the user. The above-mentioned sampling types are divided into two types: single sampling and cyclic sampling. The user can select the above two sampling types on the sampling information configuration page. The above-mentioned single sampling: When the single sampling type is selected, the user can choose immediate sampling or scheduled sampling. If the user chooses immediate sampling, the sampling data generation task will be executed immediately; if the user chooses scheduled sampling, the sampling information configuration page will display the scheduled sampling time. The user selects the sampling time, and the sampling data generation task will execute the sampling task when the selected sampling time arrives. The above-mentioned cyclic sampling task: When the user selects the cyclic sampling task, the page will display the cron expression input box, and the user can convert the sampling task execution rule into a cron expression input. The above-mentioned sampling quantity types are divided into two types: percentage and unlimited. When the user selects the percentage type, the page displays a percentage input box, and the user can enter the percentage of the extracted data by himself; when the user selects the unlimited type, there is no data upper limit when executing the sampling task.

[0092] Step S203, determining the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, calling the preset sampling inspection engine, querying the preset database based on the task name to obtain corresponding initial data.

[0093] In this embodiment, the sampling type is obtained from the basic configuration information in the sampling configuration information input by the user on the sampling information configuration page, and the task processing time is determined based on the sampling type. The above-mentioned sampling engine is a pre-created rule engine for executing sampling data generation processing. The sampling engine generally executes according to the following process: first, the task name of the sampling data generation task is obtained, and the initial data in the database is obtained based on the task name query, the sampling configuration information is obtained, and the sampling condition preprocessing is performed based on the sampling configuration information. Finally, the above-mentioned initial data is filtered based on the sampling policy conditions. The data obtained after filtering by the sampling engine is the data to be sampled corresponding to this sampling data generation task. Among them, the above-mentioned database can be a pg database.

[0094] Step S204: generating a first sampling condition based on the sampling strategy, the product name, and the business name.

[0095] In the embodiment, the sampling strategy can be acquired from the basic configuration information in the sampling configuration information input by the user on the sampling information configuration page, and the product name and the service name can be acquired from the sampling strategy condition in the sampling configuration information. The sampling strategy includes a first preset sampling strategy or a second preset sampling strategy. The specific implementation process of generating the first sampling condition based on the sampling strategy, the product name and the service name will be further described in detail in subsequent specific embodiments, and will not be described in detail here.

[0096] In step S205, the first sampling condition is preset processed based on the sampling amount type to obtain a second sampling condition.

[0097] In the embodiment, the sampling amount type can be acquired from the basic configuration information in the sampling configuration information input by the user on the sampling information configuration page. The specific implementation process of preset processing the first sampling condition based on the sampling amount type to obtain the second sampling condition will be further described in detail in subsequent specific embodiments, and will not be described in detail here.

[0098] In step S206, the initial data is data filtered based on the sampling strategy condition and the second sampling condition to obtain target data to be sampled.

[0099] In the embodiment, the sampling strategy condition includes product name, service name, data state, data result, start time and end time. The specific implementation process of data filtering the initial data based on the sampling strategy condition and the second sampling condition to obtain the target data to be sampled will be further described in detail in subsequent specific embodiments, and will not be described in detail here.

[0100] After receiving the sampling data generation task triggered by the user, this application will first display the preset sampling information configuration page, and receive the sampling configuration information entered by the user on the sampling information configuration page, and then determine the task processing time based on the sampling type, and when the current time reaches the task processing time, call the preset sampling engine, query the preset database based on the task name to obtain the corresponding initial data, and then generate the first sampling condition based on the sampling strategy, product name and business name, and then perform preset processing on the first sampling condition based on the sampling quantity type to obtain the second sampling condition, and finally perform data filtering on the initial data based on the sampling strategy condition and the second sampling condition to obtain the target data to be sampled. By adopting the solution of this application, the user only needs to enter the sampling configuration information on the page, and can use the sampling engine to automatically and quickly extract the target data to be sampled from the initial data in the database, effectively improving the generation efficiency and generation intelligence of the target data, and improving the user experience.

[0101] In some optional implementations, step S204 includes the following steps:

[0102] A corresponding business interface is obtained based on the product name and the business name.

[0103] In this embodiment, the user can select the product that needs to be reviewed for content on the spot check information configuration page. Once the user determines the product name, the data displayed in the service name drop-down box on the spot check information configuration page is all the service modules of the selected product. For example, assuming that the access platform of the electronic device is Good Car Owner, the service modules connected to the Good Car Owner platform include: user nickname module, comment module. If the user selects the product name "Good Car Owner" on the spot check information configuration page when creating the spot check data generation task, the available service names are user nickname module and comment module. If the user selects a user nickname, the corresponding access interface, i.e., the service interface, is the Good Car Owner user nickname interface.

[0104] If the sampling strategy is the first preset sampling strategy, the service interface is divided into a first number of first service interface sets according to preset priority information, and the first service interface set is stored in the preset initial sampling condition to obtain the first sampling condition.

[0105] In this embodiment, the first preset sampling strategy is specifically a strategy that prioritizes high-priority interfaces, the priority level information refers to the risk level of the interface, and the first number is 3. Based on the risk level, the business interfaces can be divided into three first business interface sets, specifically highList (high-risk set), middleList (medium-risk set), and lowList (low-risk set), and the sampling order for executing the sampling data generation task is: highList=>middleList=>lowList.

[0106] If the sampling inspection strategy is the second preset sampling inspection strategy, the service interface is divided into a second number of second service interface sets according to preset content types.

[0107] In this embodiment, the above-mentioned second preset sampling strategy is a sampling strategy of geometric execution. The above-mentioned content types include text, picture, audio, video, and integrated media, and the above-mentioned second number is 5. The business interface can be divided into five sets of text, image, audio, video, and media through the content type, that is, the above-mentioned second business interface set. If the content type of the interface in the business interface is text, the interface is divided into the text set; if the content type of the interface is picture, the interface is divided into the image set; if the content type of the interface is audio, the interface is divided into the audio set; if the content type of the interface is video, the interface is divided into the video set; if the content type of the interface is integrated media, the interface is divided into the media set.

[0108] Determine the priority of each second service interface set, and determine the data extraction ratio of each second service interface set based on the priority of each second service interface set.

[0109] In this embodiment, there is no specific limitation on the process of determining the priority of each second service interface set, and it can be set according to actual business needs. Among them, the data extraction ratio of each second service interface set is determined based on the principle that the data of the set with a high priority accounts for a high proportion. The specific implementation process of determining the data extraction ratio of each second service interface set based on the priority of each second service interface set will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated on here.

[0110] The second service interface set and the data extraction ratio are stored in the initial sampling condition to obtain the first sampling condition.

[0111] In this embodiment, the initial sampling condition is pre-constructed condition data including parameters such as the first object and the second object.

[0112] In another embodiment, the sampling strategy may further include an average execution sampling strategy. The average execution rule of the average execution sampling strategy is that, for the selected service interfaces, an equal number of samples are sampled from each interface. If the sampling strategy is an average execution sampling strategy, the service interfaces are not preprocessed and are directly stored in the initial sampling conditions to obtain the first sampling conditions.

[0113] This application obtains the corresponding business interface based on the product name and business name, and then adopts different preprocessing methods for different sampling strategies to generate the corresponding first sampling conditions, thereby ensuring the accuracy of the generation of the first sampling conditions, and is conducive to the subsequent pre-processing of the first sampling conditions based on the sampling quantity type to obtain the second sampling conditions, and then based on the sampling strategy conditions and the second sampling conditions, quickly filter out the target data to be sampled from the initial data in the database, thereby improving the efficiency of generating target data.

[0114] In some optional implementations of this embodiment, determining the data extraction ratio of each second service interface set based on the priority of each second service interface set includes the following steps:

[0115] The priority value of each second service interface set is determined based on the priority of each second service interface set.

[0116] In this embodiment, the geometric execution rule corresponding to the second preset sampling strategy is to calculate the data extraction amount of each business interface according to the expression text:image:audio:video:media=a:b:c:d:e. The above expression is explained as follows: text represents text type data, image represents picture type data, audio represents audio type data, video represents video type data, media represents integrated media type data, a represents the proportion of text type data, b represents the proportion of picture type data, c represents the proportion of audio type data, d represents the proportion of audio type data, and e represents the proportion of integrated media type data. When the sampling data generation task is executed, the above business interfaces are divided into five sets: text, picture, audio, video, and integrated media. Then, according to the above expression, the amount of data that needs to be extracted from the initial data in the database for the five sets of business interfaces is calculated. Among them, the priority value of each set of the second business interfaces can be determined by querying the pre-created priority value table. The above priority value table stores different priorities and priority values ​​with a one-to-one mapping relationship with each priority.

[0117] The sum of all the priority values ​​is calculated.

[0118] Calculate the quotient of the specified priority value and the sum value; wherein the specified priority value is the priority value of any second service interface set.

[0119] The quotient value is used as the data extraction ratio of the second service interface set corresponding to the specified priority value.

[0120] In this embodiment, the calculation process of the priority value of each second service interface set is the same as the calculation process corresponding to the above-mentioned specified priority value.

[0121] The present application determines the priority value of each second business interface set based on the priority of each second business interface set, and then can quickly and accurately determine the data extraction ratio of each second business interface set based on the obtained priority value, which is conducive to subsequently generating the first sampling condition based on the data extraction ratio, and then quickly filtering out the target data to be sampled from the initial data in the database based on the generated first sampling condition, thereby improving the efficiency of generating target data.

[0122] In some optional implementations, step S205 includes the following steps:

[0123] Determine whether the sampling quantity type is unlimited.

[0124] In this embodiment, the above-mentioned sampling quantity types are divided into two types: percentage and unlimited. When the user selects the percentage type, the page displays a percentage input box, and the user can enter the percentage of the extracted data, that is, the percentage value; when the user selects the unlimited type, there is no data upper limit when executing the sampling task.

[0125] If the sampling quantity type is unlimited, the value of the preset first variable is set to 0, and the first variable is stored in the first sampling condition to obtain the second sampling condition.

[0126] In this embodiment, a mapping relationship between the first variable with a value of 0 and the unlimited sampling quantity type is established by setting the value of the first variable to 0. The first variable may be f.

[0127] If the sampling quantity type is not unlimited, determine whether the sampling quantity type is a percentage.

[0128] If the sampling quantity type is a percentage, the value of the first variable is set to 1, and the percentage value corresponding to the sampling quantity type is assigned to the preset second variable.

[0129] In this embodiment, a mapping relationship between the first variable with a value of 1 and the sampling quantity type of percentage is constructed by setting the value of the first variable to 1. The second variable may be g.

[0130] The first variable and the second variable are stored in the first sampling inspection condition to obtain the second sampling inspection condition.

[0131] After obtaining the sampling quantity type from the basic configuration information, this application will intelligently adopt different processing methods for different sampling quantity types to generate corresponding second sampling conditions, ensuring the accuracy of the generation of the second sampling conditions, which is conducive to the subsequent rapid screening of target data to be sampled from the initial data in the database based on the sampling strategy conditions and the second sampling conditions, thereby improving the efficiency of generating target data.

[0132] In some optional implementations, step S206 includes the following steps:

[0133] Get the set of business interfaces within the second sampling condition.

[0134] In this embodiment, the service interface set may include the first service interface set or the second service interface set.

[0135] Determine whether the service interface set includes the first service interface set.

[0136] In this embodiment, it can be determined whether the highList set in the service interface set is empty. If the highList set in the service interface set is not empty, it is determined that the service interface set includes the first service interface set.

[0137] If the first business interface set is included, based on the sampling policy conditions and the preset sorting order, the initial data is filtered to obtain first data, and the first data is stored in a preset storage unit.

[0138] In this embodiment, the above-mentioned sampling inspection strategy conditions are composed of six factors: data status, data results, start time, end time, product name, and business name. Specifically, (1) the data status is divided into five types: sampled, machine-reviewed, human-reviewed, human-reviewed once, and archived. The life cycle of the data to be reviewed is summarized as the following process: machine-reviewed -> sampled -> human-reviewed -> second human-reviewed -> archived. According to the different data statuses selected, data at different life cycle stages are extracted. (2) The data results are divided into four types: passed, suspected, failed, and all result states. The data results are updated every time the data is reviewed. If the content is determined to be in violation, the data will be marked with a failed result; if the content is suspected to be in violation, the data will be marked with a suspected result; if the content is determined not to be in violation, the data will be marked with a passed result. (3) The start time startTime and the end time endTime constitute the time interval [startTime, endTime]. When executing the sampling inspection task, the data within the time interval [startTime, endTime] is extracted based on the business data reporting time. The preset sorting order is the processing order of highList set->middleList set->lowList set. The storage unit may be a unit for storing data created in the electronic device according to actual usage requirements.

[0139] Obtain the value of the first variable within the second sampling condition.

[0140] In this embodiment, the value of the first variable may include 0 or 1.

[0141] If the value of the first variable in the second sampling condition is 0, all the first data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled.

[0142] In this embodiment, the target data table may be a pool table, and the first data in the target data table is regarded as the target data to be sampled.

[0143] If the value of the first variable in the second sampling condition is 1, the value of the second variable in the second sampling condition is obtained.

[0144] In this embodiment, the value of the second variable in the second sampling condition refers to a percentage value corresponding to the sampling quantity type.

[0145] Based on the value of the second variable, data extraction processing is performed on all the first data in the storage unit to obtain second data.

[0146] In this embodiment, data extraction processing may be performed on all first data in the storage unit according to a percentage value corresponding to the sampling quantity type to obtain the second data.

[0147] The second data is stored in the target data table of the database to obtain the target data.

[0148] This application obtains a business interface set within the second sampling condition. If it is detected that the business interface set includes the first business interface set, the initial data will be filtered based on the sampling strategy conditions and the preset sorting order to obtain the first data and store it in a preset storage unit. Based on the different values ​​of the first variable within the second sampling condition, different processing methods are used to process the first data to generate the final target data to be sampled, thereby ensuring the accuracy and intelligence of the target data generation.

[0149] In some optional implementations of this embodiment, after determining whether the service interface set includes the first service interface set, the electronic device may further perform the following steps:

[0150] If the first service interface set is not included, determine whether the service interface set includes the second service interface set.

[0151] In this embodiment, it can be determined whether the text set in the service interface set is empty. If the text set in the service interface set is not empty, it is determined that the service interface set includes the second service interface set.

[0152] If the second service interface set is included, the initial data is filtered based on the sampling policy condition and the data extraction ratio to obtain third data, and the third data is stored in the storage unit.

[0153] In this embodiment, if the service interface set does not include the first service interface set or the second service interface set, the sampling strategy corresponding to the service interface set is the average execution sampling strategy, and the service interface selected in the sampling data generation task is directly obtained. Data filtering is performed based on the service interface and the initial data of the sampling strategy conditions, and the filtered data is stored in the storage unit. The subsequent processing flow can be referred to the following technical content, which will not be elaborated on here.

[0154] Obtain the value of the first variable within the second sampling condition.

[0155] In this embodiment, the value of the first variable may include 0 or 1.

[0156] If the value of the first variable in the second sampling condition is 0, all the third data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled.

[0157] In this embodiment, the third data in the target data table is regarded as the target data to be sampled.

[0158] If the value of the first variable in the second sampling condition is 1, the value of the second variable in the second sampling condition is obtained.

[0159] In this embodiment, the value of the second variable in the second sampling condition refers to a percentage value corresponding to the sampling quantity type.

[0160] Based on the value of the second variable, data extraction processing is performed on all the third data in the storage unit to obtain fourth data.

[0161] In this embodiment, data extraction processing may be performed on all third data in the storage unit according to a percentage value corresponding to the sampling quantity type to obtain the fourth data.

[0162] The fourth data is stored in the target data table of the database to obtain the target data.

[0163] This application obtains a business interface set within the second sampling condition. If it is detected that the business interface set includes the first business interface set, the initial data will be filtered based on the sampling strategy conditions and the data extraction ratio to obtain third data and store it in a preset storage unit. Based on the different values ​​of the first variable within the second sampling condition, different processing methods are used to process the third data to generate the final target data to be sampled, thereby ensuring the accuracy and intelligence of the target data generation.

[0164] In some optional implementations of this embodiment, after step S206, the electronic device may further perform the following steps:

[0165] Generate a sampling task corresponding to the target data.

[0166] In this embodiment, after the target task to be inspected is extracted from the initial data in the database based on the inspection engine, a corresponding inspection task can be further created based on the target data to review the content in the target data.

[0167] Perform the sampling inspection task.

[0168] In this embodiment, a real-time sampling inspection model for executing sampling inspection tasks may be created in advance according to actual business usage requirements, and the generated sampling inspection tasks corresponding to the target data may be executed and processed by calling the real-time sampling inspection model.

[0169] Obtain the task execution result corresponding to the sampling inspection task.

[0170] In this embodiment, after the real-time sampling inspection model completes the execution of the generated sampling inspection task corresponding to the target data, a task execution result corresponding to the sampling inspection task is generated.

[0171] The task execution results are stored and displayed.

[0172] In this embodiment, there is no limitation on the storage method of the task execution results, which can be determined based on actual usage requirements. For example, the task execution results can be stored in a database or on a blockchain. In addition, there is no limitation on the display method of the task execution results, which can be determined based on actual usage requirements. For example, the task execution results can be displayed in text form on the current interface.

[0173] After extracting the target task to be inspected from the initial data in the database based on the inspection engine, this application will further generate an inspection task corresponding to the target data, and obtain the task execution result by executing the inspection task, and store and display the task execution result, so as to quickly realize the review and processing of the content in the target data and generate corresponding result data, so that relevant users can understand the review results corresponding to the target data in a timely manner based on the task execution result, thereby improving the user experience.

[0174] It should be emphasized that in order to further ensure the privacy and security of the above target data, the above target data can also be stored in a node of a blockchain.

[0175] The blockchain referred to in this application is a new application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.

[0176] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0177] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0178] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0179] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0180] Further references Figure 3 , as a response to the above Figure 2 In order to realize the method shown in FIG, the present application provides an embodiment of a data generating device. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0181] like Figure 3As shown, the data generating device 300 of this embodiment includes: a first receiving module 301, a second receiving module 302, a query module 303, a first generating module 304, a first processing module 305 and a second processing module 306.

[0182] The first receiving module 301 is used to receive a sampling data generation task triggered by a user;

[0183] The second receiving module 302 is configured to display a preset sampling information configuration page and receive the sampling configuration information input by the user on the sampling information configuration page; wherein the sampling configuration information includes basic configuration information and sampling strategy conditions, wherein the basic configuration information includes at least the task name, sampling strategy, sampling type, and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and the business name;

[0184] The query module 303 is used to determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call the preset sampling inspection engine to query the preset database based on the task name to obtain the corresponding initial data;

[0185] A first generating module 304 is configured to generate a first sampling condition based on the sampling strategy, the product name, and the business name;

[0186] A first processing module 305 is configured to perform preset processing on the first sampling condition based on the sampling quantity type to obtain a second sampling condition;

[0187] The second processing module 306 is configured to perform data filtering processing on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain target data to be sampled.

[0188] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0189] In some optional implementations of this embodiment, the first generating module 304 includes:

[0190] A first acquisition submodule, configured to acquire a corresponding business interface based on the product name and the business name;

[0191] A first division submodule is configured to, if the sampling inspection strategy is a first preset sampling inspection strategy, divide the service interfaces into a first number of first service interface sets according to preset priority information, and store the first service interface sets in a preset initial sampling inspection condition to obtain the first sampling inspection condition;

[0192] A second division submodule is configured to divide the service interface into a second number of second service interface sets according to a preset content type if the sampling inspection strategy is a second preset sampling inspection strategy;

[0193] a determination submodule, configured to determine the priority of each second service interface set, and determine the data extraction ratio of each second service interface set based on the priority of each second service interface set;

[0194] The first generating submodule is used to store the second service interface set and the data extraction ratio in the initial sampling condition to obtain the first sampling condition.

[0195] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0196] In some optional implementations of this embodiment, the determining submodule includes:

[0197] a determining unit, configured to determine a priority value of each second service interface set based on the priority of each second service interface set;

[0198] a first calculation unit, configured to calculate a sum of all the priority values;

[0199] A second calculation unit is configured to calculate a quotient of a specified priority value and the sum value; wherein the specified priority value is a priority value of any second service interface set;

[0200] The determining unit is configured to use the quotient as a data extraction ratio of a second service interface set corresponding to the specified priority value.

[0201] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the above-mentioned embodiment, and are not described again here.

[0202] In some optional implementations of this embodiment, the first processing module 305 includes:

[0203] The first judgment submodule is used to judge whether the sampling quantity type is unlimited;

[0204] A second generating submodule is configured to, if the sampling quantity type is unlimited, set the value of the preset first variable to 0, and store the first variable in the first sampling condition to obtain the second sampling condition;

[0205] The second judgment submodule is used to judge whether the sampling quantity type is a percentage if the sampling quantity type is not unlimited;

[0206] A first processing submodule is configured to set the value of the first variable to 1 if the sampling quantity type is a percentage, and assign the percentage value corresponding to the sampling quantity type to a preset second variable;

[0207] The third generating submodule is used to store the first variable and the second variable into the first sampling condition to obtain the second sampling condition.

[0208] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0209] In some optional implementations of this embodiment, the second processing module 306 includes:

[0210] A second acquisition submodule is used to obtain a set of business interfaces within the second sampling condition;

[0211] A third judgment submodule, configured to judge whether the service interface set includes the first service interface set;

[0212] A second processing submodule is configured to, if the first service interface set is included, perform data filtering on the initial data based on the sampling policy conditions and a preset sorting order to obtain first data, and store the first data in a preset storage unit;

[0213] a third acquisition submodule, configured to obtain a value of the first variable within the second sampling condition;

[0214] a third processing submodule, configured to store all the first data in the storage unit into a target data table in the database to obtain the target data to be sampled if the value of the first variable in the second sampling condition is 0;

[0215] a fourth acquisition submodule, configured to acquire a value of a second variable within the second sampling condition if the value of the first variable within the second sampling condition is 1;

[0216] a first extraction submodule, configured to extract all the first data in the storage unit based on the value of the second variable to obtain second data;

[0217] The fourth generating submodule is used to store the second data into the target data table of the database to obtain the target data.

[0218] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0219] In some optional implementations of this embodiment, the second processing module 306 includes:

[0220] A fourth judgment submodule is configured to judge whether the service interface set includes the second service interface set if the first service interface set is not included;

[0221] a fourth processing submodule, configured to, if the second service interface set is included, perform data filtering on the initial data based on the sampling policy condition and the data extraction ratio to obtain third data, and store the third data in the storage unit;

[0222] a fifth acquisition submodule, configured to obtain a value of the first variable within the second sampling condition;

[0223] a fifth generating submodule, configured to store all the third data in the storage unit into the target data table of the database to obtain the target data to be sampled if the value of the first variable in the second sampling condition is 0;

[0224] a sixth acquisition submodule, configured to acquire a value of a second variable within the second sampling condition if the value of the first variable within the second sampling condition is 1;

[0225] a fifth processing submodule, configured to extract all the third data in the storage unit based on the value of the second variable to obtain fourth data;

[0226] The sixth generating submodule is used to store the fourth data into the target data table of the database to obtain the target data.

[0227] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0228] In some optional implementations of this embodiment, the data generating device further includes:

[0229] A second generating module is used to generate a sampling inspection task corresponding to the target data;

[0230] An execution module, used for executing the sampling inspection task;

[0231] An acquisition module is used to obtain the task execution result corresponding to the sampling inspection task;

[0232] The third processing module is used to store and display the task execution results.

[0233] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the data generation method in the aforementioned embodiment, and are not described again here.

[0234] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0235] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components 41-43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0236] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0237] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (SMC), a secure digital (SD) card, a flash memory card, etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the data generation method. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0238] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions stored in the memory 41 or process data, such as computer-readable instructions for executing the data generation method.

[0239] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0240] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0241] In the embodiments of this application,.

[0242] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the data generation method as described above.

[0243] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0244] In the embodiments of the present application,

[0245] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and the necessary general hardware platform, of course, they can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, an optical disk), and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the various embodiments of the present application.

[0246] Obviously, the above-described embodiments are only some of the embodiments of the present application, not all the embodiments, and the preferred embodiments of the present application are given in the drawings, but do not limit the patent scope of the present application. The present application can be implemented in many different forms, and conversely, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing specific embodiments, or equivalently replace some of the technical features. Any equivalent structure made by using the content of the specification and drawings, directly or indirectly applied to other related technical fields, is also within the scope of the patent protection of the present application.

Claims

1. A data generation method, characterized in that: The steps include: Receive user-triggered sampling data generation tasks; Displaying a preset sampling information configuration page and receiving the sampling configuration information input by the user on the sampling information configuration page; wherein the sampling configuration information includes basic configuration information and sampling strategy conditions, wherein the basic configuration information includes at least the task name, sampling strategy, sampling type, and sampling quantity type of the sampling data generation task, and the sampling strategy conditions include at least the product name and business name; Determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine, and query a preset database based on the task name to obtain corresponding initial data; Generate a first sampling condition based on the sampling strategy, the product name, and the business name; Based on the sampling quantity type, presetting the first sampling condition to obtain a second sampling condition; Performing data filtering on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain target data to be sampled; The step of generating the first sampling condition based on the sampling strategy, the product name, and the service name specifically includes: Acquire a corresponding business interface based on the product name and the business name; If the sampling inspection strategy is the first preset sampling inspection strategy, the service interfaces are divided into a first number of first service interface sets according to preset priority information, and the first service interface sets are stored in the preset initial sampling inspection conditions to obtain the first sampling inspection conditions; If the sampling inspection strategy is a second preset sampling inspection strategy, dividing the service interface into a second number of second service interface sets according to preset content types; Determining the priority of each second service interface set, and determining the data extraction ratio of each second service interface set based on the priority of each second service interface set; Storing the second service interface set and the data extraction ratio in the initial sampling condition to obtain the first sampling condition; The step of presetting the first sampling condition based on the sampling quantity type to obtain the second sampling condition specifically includes: Determine whether the sampling quantity type is unlimited; If the sampling quantity type is unlimited, the value of the preset first variable is set to 0, and the first variable is stored in the first sampling condition to obtain the second sampling condition; If the sampling quantity type is not unlimited, determine whether the sampling quantity type is percentage; If the sampling quantity type is a percentage, the value of the first variable is set to 1, and the percentage value corresponding to the sampling quantity type is assigned to the preset second variable; The first variable and the second variable are stored in the first sampling inspection condition to obtain the second sampling inspection condition.

2. The data generation method according to claim 1, wherein: The step of determining the data extraction ratio of each second service interface set based on the priority of each second service interface set specifically includes: Determining a priority value of each second service interface set based on the priority of each second service interface set; Calculating the sum of all the priority values; Calculating a quotient of a specified priority value and the sum value; wherein the specified priority value is a priority value of any second service interface set; The quotient value is used as the data extraction ratio of the second service interface set corresponding to the specified priority value.

3. The data generation method according to claim 1, wherein: The step of performing data filtering processing on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain the target data to be sampled specifically includes: Obtain the business interface set within the second sampling condition; Determining whether the service interface set includes the first service interface set; If the first service interface set is included, based on the sampling policy conditions and the preset sorting order, filtering the initial data to obtain first data, and storing the first data in a preset storage unit; Obtaining the value of the first variable within the second sampling condition; If the value of the first variable in the second sampling condition is 0, all the first data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled; If the value of the first variable in the second sampling condition is 1, obtain the value of the second variable in the second sampling condition; performing data extraction processing on all the first data in the storage unit based on the value of the second variable to obtain second data; The second data is stored in the target data table of the database to obtain the target data.

4. The data generation method according to claim 3, characterized in that After the step of determining whether the service interface set includes the first service interface set, the method further includes: If the first service interface set is not included, determining whether the service interface set includes the second service interface set; If the second service interface set is included, performing data filtering processing on the initial data based on the sampling policy condition and the data extraction ratio to obtain third data, and storing the third data in the storage unit; Obtaining the value of the first variable within the second sampling condition; If the value of the first variable in the second sampling condition is 0, all the third data in the storage unit are stored in the target data table of the database to obtain the target data to be sampled; If the value of the first variable in the second sampling condition is 1, obtain the value of the second variable in the second sampling condition; performing data extraction processing on all the third data in the storage unit based on the value of the second variable to obtain fourth data; The fourth data is stored in the target data table of the database to obtain the target data.

5. The data generation method according to claim 1, wherein: After the step of filtering the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain the target data to be sampled, the method further includes: generating a sampling inspection task corresponding to the target data; Perform the sampling inspection task; Obtaining the task execution result corresponding to the sampling inspection task; The task execution results are stored and displayed.

6. A data generating device, characterized in that: include: A first receiving module is used to receive a sampling data generation task triggered by a user; a second receiving module, configured to display a preset sampling inspection information configuration page and receive the sampling inspection configuration information input by the user on the sampling inspection information configuration page; wherein the sampling inspection configuration information includes basic configuration information and sampling inspection strategy conditions, wherein the basic configuration information includes at least the task name, sampling inspection strategy, sampling inspection type, and sampling inspection quantity type of the sampling inspection data generation task, and the sampling inspection strategy conditions include at least the product name and the business name; A query module is used to determine the task processing time based on the sampling inspection type, and when the current time reaches the task processing time, call a preset sampling inspection engine to query a preset database based on the task name to obtain corresponding initial data; A first generating module, configured to generate a first sampling condition based on the sampling strategy, the product name, and the business name; A first processing module, configured to perform preset processing on the first sampling condition based on the sampling quantity type to obtain a second sampling condition; A second processing module is used to perform data filtering processing on the initial data based on the sampling inspection strategy condition and the second sampling inspection condition to obtain target data to be sampled; The first generation module includes: A first acquisition submodule, configured to acquire a corresponding business interface based on the product name and the business name; A first division submodule is configured to, if the sampling inspection strategy is a first preset sampling inspection strategy, divide the service interfaces into a first number of first service interface sets according to preset priority information, and store the first service interface sets in a preset initial sampling inspection condition to obtain the first sampling inspection condition; A second division submodule is configured to divide the service interface into a second number of second service interface sets according to a preset content type if the sampling inspection strategy is a second preset sampling inspection strategy; a determination submodule, configured to determine the priority of each second service interface set, and determine the data extraction ratio of each second service interface set based on the priority of each second service interface set; A first generating submodule, configured to store the second service interface set and the data extraction ratio in the initial sampling condition to obtain the first sampling condition; The first processing module includes: The first judgment submodule is used to judge whether the sampling quantity type is unlimited; A second generating submodule is configured to, if the sampling quantity type is unlimited, set the value of the preset first variable to 0, and store the first variable in the first sampling condition to obtain the second sampling condition; The second judgment submodule is used to judge whether the sampling quantity type is a percentage if the sampling quantity type is not unlimited; A first processing submodule is configured to set the value of the first variable to 1 if the sampling quantity type is a percentage, and assign the percentage value corresponding to the sampling quantity type to a preset second variable; The third generating submodule is used to store the first variable and the second variable into the first sampling condition to obtain the second sampling condition.

7. A computer device comprising a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the data generation method according to any one of claims 1 to 5 when executing the computer-readable instructions.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the data generation method according to any one of claims 1 to 5.

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