Performance environment data generation method and device, computer equipment and storage medium

Abstract

The embodiment of the invention belongs to the field of research and development management, and relates to a performance environment data generation method, which comprises the following steps: acquiring to-be-tested data and corresponding test configuration information thereof; testing the to-be-tested data according to the test configuration information in the test environment, and obtaining a data link according to the tested data; restoring the data link to the performance environment, and verifying the restored data link to obtain a verification result; when the verification result is that verification is passed, distribution information of seed data is obtained, and the seed data comprises to-be-tested data; and performing data generation based on the distribution information to obtain performance environment data. The invention further provides a performance environment data generation device, computer equipment and a storage medium. The accuracy of the generated performance environment data is improved.

Description

Technical Field

[0001] The present application relates to the field of R&D management technology, and in particular to a method, device, computer equipment and storage medium for generating performance environment data. Background Art

[0002] When developing a pharmaceutical e-commerce platform, performance testing is a key step in ensuring the stability and scalability of the platform. It is usually used to evaluate the capacity of the online system. There are some problems with existing performance testing. First, if online data is directly operated, a large amount of dirty data will be generated, which will increase the complexity of database cleaning and even cause online accidents. In addition, the existence of dirty data will affect subsequent data verification and cause database query performance to deteriorate. In order to avoid these problems, it is usually necessary to generate data in a dedicated performance environment.

[0003] Existing performance environment data generation methods often rely on manual creation, which is not only time-consuming and labor-intensive, but also difficult to ensure the accuracy and comprehensiveness of the data. In particular, the data structure of the pharmaceutical e-commerce platform is complex, involving many commodity attributes and strong correlations. Manually generated data often lacks authenticity and cannot fully simulate real business scenarios. This not only reduces the credibility of performance data, but may also affect the accuracy of performance test results. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a method, apparatus, computer device and storage medium for generating performance environment data to solve the problem of low accuracy of the generated performance environment data.

[0005] In order to solve the above technical problems, the embodiment of the present application provides a method for generating performance environment data, which adopts the following technical solution:

[0006] Obtain the data to be tested and its corresponding test configuration information;

[0007] Testing the data to be tested according to the test configuration information in a test environment, and obtaining a data link according to the performed test;

[0008] Restoring the data link to the performance environment, and verifying the restored data link to obtain a verification result;

[0009] When the verification result is that the verification is passed, obtaining distribution information of seed data, wherein the seed data includes the data to be tested;

[0010] Data is generated based on the distribution information to obtain performance environment data.

[0011] In order to solve the above technical problems, the embodiment of the present application further provides a performance environment data generation device, which adopts the following technical solution:

[0012] The test acquisition module is used to obtain the test data and its corresponding test configuration information;

[0013] A data testing module, used to test the data to be tested according to the test configuration information in a test environment, and obtain a data link according to the performed test;

[0014] A restoration verification module, used to restore the data link to the performance environment, and verify the restored data link to obtain a verification result;

[0015] A distribution acquisition module, used for acquiring distribution information of seed data when the verification result is verification passed, wherein the seed data includes the data to be tested;

[0016] The data generation module is used to generate data based on the distribution information to obtain performance environment data.

[0017] 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:

[0018] Obtain the data to be tested and its corresponding test configuration information;

[0019] Testing the data to be tested according to the test configuration information in a test environment, and obtaining a data link according to the performed test;

[0020] Restoring the data link to the performance environment, and verifying the restored data link to obtain a verification result;

[0021] When the verification result is that the verification is passed, obtaining distribution information of seed data, wherein the seed data includes the data to be tested;

[0022] Data is generated based on the distribution information to obtain performance environment data.

[0023] 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:

[0024] Obtain the data to be tested and its corresponding test configuration information;

[0025] Testing the data to be tested according to the test configuration information in a test environment, and obtaining a data link according to the performed test;

[0026] Restoring the data link to the performance environment, and verifying the restored data link to obtain a verification result;

[0027] When the verification result is that the verification is passed, obtaining distribution information of seed data, wherein the seed data includes the data to be tested;

[0028] Data is generated based on the distribution information to obtain performance environment data.

[0029] Compared with the prior art, the embodiments of the present application have the following beneficial effects: obtaining the data to be tested and its test configuration information, avoiding the inaccuracy and incompleteness that may be caused by manually creating data; verifying and obtaining data links in the test environment, ensuring the accuracy and consistency of the data restored to the performance environment, and reducing the risk of database performance degradation caused by dirty data; the performance environment data generated based on the distribution information of the seed data ensures the authenticity and diversity of the data, can fully simulate complex business scenarios, improve the efficiency of data generation, and also improve the accuracy and reliability of performance testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0032] Figure 2 is a flow chart of an embodiment of a method for generating performance environment data according to the present application;

[0033] Figure 3 is a structural schematic diagram of an embodiment of a performance environment data generating device according to the present application;

[0034] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0036] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0037] 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.

[0038] like Figure 1 As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables.

[0039] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0040] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, the tablet computer 1012 or the mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0041] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0042] It should be noted that the performance environment data generation method provided in the embodiment of the present application is generally executed by a server, and accordingly, the performance environment data generation device is generally set in the server.

[0043] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0044] Continue to refer Figure 2 , shows a flow chart of an embodiment of a method for generating performance environment data according to the present application. The method for generating performance environment data comprises the following steps:

[0045] Step S201, obtaining the data to be tested and its corresponding test configuration information.

[0046] In this embodiment, the performance environment data generation method is executed on the electronic device (eg Figure 1 The server shown in the figure) can communicate with the terminal device through a wired connection or a wireless connection. It should be noted that the above wireless connection method may include but is not limited to 3G / 4G / 5G connection, Wi-Fi connection, Bluetooth connection, Wi MAX connection, Zigbee connection, UWB (Ultra Wi-Fi Band) connection, and other wireless connection methods currently known or to be developed in the future.

[0047] Specifically, the data to be tested and its corresponding test configuration information are obtained. The data to be tested is real or approximately real data that is prepared in advance and is representative and complete, and is used to run the method to be tested in the preliminary performance testing phase. The data to be tested can come from a real production environment, historical data, or manually constructed data.

[0048] The test configuration information is the configuration information required when performing an initial performance test based on the data to be tested.

[0049] Furthermore, the above step S201 may include: obtaining the data to be tested and its corresponding method to be tested; obtaining the Java package on which the method to be tested depends; obtaining database dependency information in the current project through Sonar; and determining the obtained method to be tested, Java package and database dependency information as the test configuration information corresponding to the data to be tested.

[0050] Specifically, obtain the data to be tested and its related methods to be tested for preliminary performance testing. The data to be tested is sample data closely related to the actual business, which can truly reflect the performance of the system in the test. The method to be tested refers to the Java method to be tested, that is, the specific code method required for performance analysis and / or data generation during performance testing. It is a piece of business logic in the software system, such as processing the product data of the medical mall, user transactions and other operations.

[0051] Each method under test may call other Java packages and libraries when executed. This step takes into account all necessary dependencies so that the method under test can be successfully called in the test environment and performance environment to avoid test failures due to missing dependencies.

[0052] Sona is a static code analysis tool that can identify database dependencies in the current Java project. Through Sona, you can obtain database connection information and other related information to provide support for subsequent database access and ensure that the test can proceed smoothly.

[0053] After completing the collection of the above information, integrate all relevant information together to form complete test configuration information, ensuring that this information can be relied upon to verify the performance of the system during performance testing.

[0054] In this embodiment, the efficiency and accuracy of the performance test are improved by obtaining the data to be tested and its test configuration information. First, the data to be tested and its corresponding method to be tested are obtained, and then the Java package and database dependency information required by the method to be tested are integrated to avoid test failures due to lack of dependencies. Finally, the test configuration information is generated to ensure the accuracy of the performance test results.

[0055] Step S202: testing the data to be tested in the test environment according to the test configuration information, and obtaining a data link according to the performed test.

[0056] Specifically, in the test environment, the test configuration information is used to conduct preliminary performance tests on the data to be tested. The test verifies the function of the data to be tested and records the data access link to form a complete data flow. This is the basis for building performance environment data.

[0057] Furthermore, the above step S202 may include: in the test environment, calling the method to be tested based on the data to be tested and the Java package to perform the test, and accessing the database through the database dependency information to obtain database access information; and generating a data link based on the database access information.

[0058] Specifically, in the test environment, the data to be tested and the relevant Java packages are used to execute the predefined methods to be tested, simulate real business operations, and evaluate the performance of the system under specific conditions.

[0059] When calling the method to be tested, it is necessary to interact with the database to obtain or update data. Through the previously obtained database dependency information, the corresponding database can be connected and accessed to ensure that the results obtained from the database can reflect the actual situation and provide accurate data support for subsequent analysis.

[0060] After accessing the database, all relevant database interaction information is recorded, including the executed SQL queries, the primary key of the acquired data and its field attributes, etc. This information constitutes a complete data link that can describe how data flows and changes in a specific business process, providing a basis for subsequent data restoration and performance verification.

[0061] In this embodiment, the accuracy and reliability of performance testing are improved based on the call of the data to be tested and the Java package in the test environment; through the testing in the test environment, the performance of the system in processing actual business can be simulated to ensure the consistency of the test results with the actual operating environment; the database is accessed by using database dependency information to ensure the smooth data interaction, and the generated data link provides a clear perspective for subsequent analysis and verification, making the performance evaluation more systematic and scientific.

[0062] Step S203: restore the data link to the performance environment, and verify the restored data link to obtain a verification result.

[0063] Specifically, the data link is restored from the test environment to the performance environment on a one-to-one basis, and the database table and field information recorded in the data link is inserted into the database table of the corresponding performance environment, so as to evaluate the system performance under the most realistic conditions possible. In this process, it is necessary to ensure the consistency of the restored data with the source data, and confirm the success of the restoration through the verification mechanism to eliminate potential errors.

[0064] Then run the method in the performance environment, verify the inserted data, and check whether the results of running in the performance environment are consistent with those in the test environment.

[0065] Furthermore, the above-mentioned step of verifying the restored data link and obtaining the verification result may include: in a performance environment, testing the data to be tested according to the test configuration information to obtain the test result; comparing the test result obtained in the performance environment with the test result obtained in the test environment, and generating a verification result based on the comparison result.

[0066] Specifically, after restoring the data link to the performance environment, the acquired test configuration information will be used to retest the data to be tested, ensuring that the system reproduces the test scenario in the performance environment, and evaluates the data to be tested through specific parameters and configurations to obtain actual test results.

[0067] After the test is completed, the test results obtained in the performance environment are compared in detail with the results obtained in the test environment. Confirm whether the system processes and responds to the same data in the two environments. This comparison is an important step to ensure the successful restoration of the data link and can verify the accuracy and integrity of the data.

[0068] Generate verification results based on the comparison results. If the test results in the two environments are consistent, it means that the data link restoration is successful and the system's operating status in the performance environment is consistent with expectations; if they are inconsistent, you need to recheck the data link restoration process.

[0069] In this embodiment, the data to be tested is tested in the performance environment and compared with the results of the test environment, which enhances the credibility and effectiveness of the data restoration process and ensures that tests performed in different environments can obtain consistent results, thereby verifying the accuracy and completeness of the data link and avoiding performance analysis deviations caused by data errors.

[0070] Step S204, when the verification result is verification passed, obtaining distribution information of seed data, the seed data includes the data to be tested.

[0071] Specifically, when the verification result is verification passed, confirming that the data restoration is successful, the system will analyze the characteristics of the seed data and extract its distribution information.

[0072] Furthermore, before the above step of obtaining the distribution information of the seed data, it may also include: obtaining the seed data and performing integrity processing on the seed data; performing accuracy processing on the seed data after the integrity processing; performing consistency processing on the seed data after the accuracy processing; and formatting the seed data after the consistency processing.

[0073] Specifically, seed data is obtained. Seed data is the basis for generating performance environment data. The data to be tested can be used as seed data, or other data containing real business attributes and characteristics can be obtained as seed data.

[0074] In one embodiment, the seed data mainly includes the product attributes of the medicines in the medical mall, including: spu id, sku id, product name, product price, unified code, disease id, generic name, brand name, packaging specifications, manufacturer, drug status, sales volume and other attributes.

[0075] After obtaining the seed data, first perform integrity processing on the seed data to ensure that all necessary data items are collected correctly and there is no missing data. The quantity and type of the data can be checked. If there is incomplete data, the data can be deleted or filled. For example, if the drug status is missing, the sales volume of the product can be estimated through other data.

[0076] Next, the data is processed for accuracy to check whether the data is correct, whether there are errors or outliers, and the data can be deleted, modified, or added. For example, if the price of a product is negative, it needs to be converted to a positive number or converted to a positive number. This process is designed to ensure that all data items reflect the actual situation and eliminate potential errors.

[0077] The seed data after accuracy processing is then processed for consistency to ensure the coordination of the seed data across dimensions and data sets. For example, the same data item should be consistent in different records to avoid data conflicts caused by format or unit differences. You can choose to merge or rename inconsistent data.

[0078] Format the seed data after consistency processing to ensure that all seed data conform to the predetermined data format standard. Formatting can also include organizing and arranging the seed data according to SPU ID, SKU ID, etc. for subsequent data analysis and processing.

[0079] In this embodiment, the seed data is processed for integrity, accuracy, consistency and formatting, thereby improving the overall level of data quality; integrity processing ensures the comprehensiveness of the data and avoids analysis bias caused by data missing; accuracy processing eliminates potential errors in the data and improves the credibility of the data; consistency processing ensures coordination between different data sources and reduces the risk of misjudgment caused by data conflicts; formatting processing provides a good foundation for subsequent data analysis, making the generated performance environment data more in line with actual needs; this systematic data processing flow improves the reliability of generated data.

[0080] Furthermore, the step of obtaining the distribution information of the seed data may include: performing statistical analysis on the seed data to obtain the distribution information; or performing cluster analysis on the seed data to obtain the distribution information.

[0081] Specifically, statistical analysis is performed on the seed data to obtain its distribution characteristics. Statistical analysis usually includes calculating the mean, maximum, minimum, median, standard deviation, etc. These statistics reflect the concentration and dispersion of seed data in certain aspects. For example, based on statistical analysis of data, it is possible to determine the approximate range of data values, mainstream trends, and whether there are abnormal data points. It can help design more reasonable simulation data so that it is as close to the actual business situation as possible when testing in a performance environment.

[0082] In addition to simple statistical analysis, more advanced grouping processing of data can be performed through cluster analysis (such as K-means clustering algorithm). Cluster analysis can group seed data according to certain specific similarity characteristics to discover the natural structure in the data set. For example, by analyzing the characteristic distribution of the data, similar product attributes are classified into a cluster. This helps to simulate complex data relationships more accurately. The generated data is not only more similar to the real environment, but also reflects the regularity within a specific data set. The clustering results can be visualized using a scatter plot, and different clusters are represented by different colors.

[0083] The data distribution information generated through statistical analysis or cluster analysis will provide a basic basis for subsequent data generation steps, thereby ensuring that the generated data is more representative and reasonable.

[0084] In this embodiment, the statistical analysis method can effectively reflect the overall characteristics of the data, ensure that the generated data can cover the important data range, and avoid data deviation; cluster analysis classifies data with high similarity, revealing the implicit structure and rules within the data, making the generated data more in line with actual business scenarios; using statistical analysis or cluster analysis can more accurately obtain the distribution information of seed data, generate performance data that is closer to the real environment, and improve the authenticity and effectiveness of performance testing.

[0085] Step S205: Generate data based on the distribution information to obtain performance environment data.

[0086] Specifically, new performance environment data is generated based on the collected distribution information. The generated performance environment data not only has real business attributes, but can also be used for subsequent performance testing to ensure the effectiveness and reliability of the test.

[0087] In this embodiment, the data to be tested and its test configuration information are obtained, thereby avoiding the inaccuracy and incompleteness that may be caused by manually creating data; verification is performed in the test environment and the data link is obtained, thereby ensuring the accuracy and consistency of the data restored to the performance environment and reducing the risk of database performance degradation caused by dirty data; the performance environment data generated based on the distribution information of the seed data ensures the authenticity and diversity of the data, can fully simulate complex business scenarios, improve the efficiency of data generation, and also enhance the accuracy and reliability of performance testing.

[0088] It should be emphasized that in order to further ensure the privacy and security of the above seed data, the above seed data can also be stored in a node of a blockchain.

[0089] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0090] 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 obtain the best results.

[0091] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0092] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0093] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence 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 a part of the steps in the flowchart 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 part of the sub-steps or stages of other steps.

[0094] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of a device for generating performance environment data. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0095] like Figure 3As shown, the performance environment data generating device 300 described in this embodiment includes: a test acquisition module 301, a data testing module 302, a restoration verification module 303, a distribution acquisition module 304 and a data generation module 305, wherein:

[0096] The test acquisition module 301 is used to acquire the test data and its corresponding test configuration information.

[0097] The data testing module 302 is used to test the data to be tested according to the test configuration information in the test environment, and obtain the data link according to the performed test.

[0098] The restoration verification module 303 is used to restore the data link to the performance environment and verify the restored data link to obtain a verification result.

[0099] The distribution acquisition module 304 is used to acquire distribution information of seed data when the verification result is verification passed, where the seed data includes the data to be tested.

[0100] The data generation module 305 is used to generate data based on the distribution information to obtain performance environment data.

[0101] In this embodiment, the data to be tested and its test configuration information are obtained, thereby avoiding the inaccuracy and incompleteness that may be caused by manually creating data; verification is performed in the test environment and the data link is obtained, thereby ensuring the accuracy and consistency of the data restored to the performance environment and reducing the risk of database performance degradation caused by dirty data; the performance environment data generated based on the distribution information of the seed data ensures the authenticity and diversity of the data, can fully simulate complex business scenarios, improve the efficiency of data generation, and also enhance the accuracy and reliability of performance testing.

[0102] In some optional implementations of this embodiment, the to-be-tested acquisition module 301 may also be used to:

[0103] Get the data to be tested and its corresponding method to be tested.

[0104] Get the Java packages that the method to be tested depends on.

[0105] Get database dependency information in the current project through Sonar.

[0106] The obtained method to be tested, Java package and database dependency information are determined as the test configuration information corresponding to the data to be tested.

[0107] In some optional implementations of this embodiment, the data testing module 302 may also be used to:

[0108] In the test environment, the method to be tested is called based on the data to be tested and the Java package to perform the test, and the database is accessed through the database dependency information to obtain the database access information.

[0109] Generate a data link based on the database access information.

[0110] In some optional implementations of this embodiment, the restoration verification module 303 may also be used to:

[0111] In the performance environment, the data to be tested is tested according to the test configuration information to obtain the test result.

[0112] The test results obtained in the performance environment are compared with the test results obtained in the test environment, and verification results are generated based on the comparison results.

[0113] In some optional implementations of this embodiment, the performance environment data generating device 300 may further include:

[0114] The integrity processing module is used to obtain seed data and perform integrity processing on the seed data.

[0115] The accuracy processing module is used to perform accuracy processing on the seed data after integrity processing.

[0116] The consistency processing module is used to perform consistency processing on the seed data after accuracy processing.

[0117] The formatting processing module is used to format the seed data after consistency processing.

[0118] In some optional implementations of this embodiment, the distribution acquisition module 304 may include:

[0119] The statistical analysis submodule is used to perform statistical analysis on the seed data to obtain distribution information.

[0120] The cluster analysis submodule is used to perform cluster analysis on seed data to obtain distribution information.

[0121] 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.

[0122] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected and communicated through a system bus. It should be noted that the figure only shows a computer device 4 having a memory 41, a processor 42, and a network interface 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 a microprocessor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital processor (DSP), an embedded device, etc.

[0123] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0124] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), 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, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a 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, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 4. 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 performance environment data generation method, etc. 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.

[0125] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. 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 run computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for running the performance environment data generation method.

[0126] 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.

[0127] The computer device provided in this embodiment can execute the above-mentioned performance environment data generation method. Here, the performance environment data generation method can be the performance environment data generation method of each of the above-mentioned embodiments.

[0128] In this embodiment, the data to be tested and its test configuration information are obtained, thereby avoiding the inaccuracy and incompleteness that may be caused by manually creating data; verification is performed in the test environment and the data link is obtained, thereby ensuring the accuracy and consistency of the data restored to the performance environment and reducing the risk of database performance degradation caused by dirty data; the performance environment data generated based on the distribution information of the seed data ensures the authenticity and diversity of the data, can fully simulate complex business scenarios, improve the efficiency of data generation, and also enhance the accuracy and reliability of performance testing.

[0129] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium 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 performance environment data generation method as described above.

[0130] In this embodiment, the data to be tested and its test configuration information are obtained, thereby avoiding the inaccuracy and incompleteness that may be caused by manually creating data; verification is performed in the test environment and the data link is obtained, thereby ensuring the accuracy and consistency of the data restored to the performance environment and reducing the risk of database performance degradation caused by dirty data; the performance environment data generated based on the distribution information of the seed data ensures the authenticity and diversity of the data, can fully simulate complex business scenarios, improve the efficiency of data generation, and also enhance the accuracy and reliability of performance testing.

[0131] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0132] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for generating performance environment data, characterized in that: The steps include: Obtain the data to be tested and its corresponding test configuration information; Testing the data to be tested according to the test configuration information in a test environment, and obtaining a data link according to the performed test; Restoring the data link to the performance environment, and verifying the restored data link to obtain a verification result; When the verification result is that the verification is passed, obtaining distribution information of seed data, wherein the seed data includes the data to be tested; Data is generated based on the distribution information to obtain performance environment data.

2. The method for generating performance environment data according to claim 1, characterized in that: The step of obtaining the test data and its corresponding test configuration information comprises: Obtain the data to be tested and its corresponding method to be tested; Get the Java package that the method to be tested depends on; Get database dependency information in the current project through Sonar; The acquired method to be tested, Java package and database dependency information are determined as the test configuration information corresponding to the data to be tested.

3. The method for generating performance environment data according to claim 2, characterized in that: The step of testing the data to be tested according to the test configuration information in the test environment and obtaining the data link according to the performed test comprises: In a test environment, the method to be tested is called based on the data to be tested and the Java package to perform the test, and a database is accessed through the database dependency information to obtain database access information; A data link is generated based on the database access information.

4. The method for generating performance environment data according to claim 1, characterized in that: The step of verifying the restored data link to obtain a verification result includes: In the performance environment, testing the data to be tested according to the test configuration information to obtain a test result; The test results obtained in the performance environment are compared with the test results obtained in the test environment, and a verification result is generated based on the comparison result.

5. The method for generating performance environment data according to claim 1, characterized in that: Before the step of obtaining the distribution information of the seed data, the method further includes: Obtaining seed data and performing integrity processing on the seed data; Performing accuracy processing on the seed data after the integrity processing; Performing consistency processing on the seed data after the accuracy processing; The seed data after the consistency processing is formatted.

6. The method for generating performance environment data according to claim 1, characterized in that: The step of obtaining distribution information of seed data comprises: Performing statistical analysis on the seed data to obtain distribution information; or, Cluster analysis is performed on the seed data to obtain distribution information.

7. A performance environment data generating device, characterized in that: include: The test acquisition module is used to obtain the test data and its corresponding test configuration information; A data testing module, used to test the data to be tested according to the test configuration information in a test environment, and obtain a data link according to the performed test; A restoration verification module, used to restore the data link to the performance environment, and verify the restored data link to obtain a verification result; A distribution acquisition module, used for acquiring distribution information of seed data when the verification result is verification passed, wherein the seed data includes the data to be tested; The data generation module is used to generate data based on the distribution information to obtain performance environment data.

8. The performance environment data generating device according to claim 7, characterized in that: The distribution acquisition module includes: A statistical analysis submodule, used to perform statistical analysis on the seed data to obtain distribution information; The cluster analysis submodule is used to perform cluster analysis on the seed data to obtain distribution information.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the performance environment data generating method as described in any one of claims 1 to 6 are implemented.

10. 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 performance environment data generating method according to any one of claims 1 to 6.

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