CN116680188A - Data processing method, device, equipment and computer readable storage medium - Google Patents
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Abstract
The application discloses a data processing method, a device, equipment and a computer readable storage medium, which are suitable for a banking and finance system, an actual production data set is formed by collecting required actual production data through configuration time and fields in a target business scene, the change trend of the actual production data of different preset dimensions and time spans in the actual production data set is analyzed, a data change trend report of the target business scene is formed, the analysis time of test data required by the target business scene is saved, the performance test efficiency of the target business scene is improved, meanwhile, the preset dimensions can be adaptively adjusted according to actual conditions, the use is convenient, and the technical problems that the test data called in the prior art are difficult to match and attach with the conditions of the actual production environment in the operation process are solved.
Description
Technical Field
The present application relates to the technical field of financial science and technology, and in particular, to a data processing method, apparatus, device, and computer readable storage medium.
Background
In a banking and financial system, the concurrency of business data of systems in different time periods is greatly different, and the performance pressure measurement of the system is an important test link.
In the existing performance pressure test process, production data are often required to be analyzed when performance test data are constructed, and data required by the performance pressure test are divided into two types: one is execution data and one is base data.
The underlying data is typically resolved by periodically importing the produced incremental data into a database of the performance test environment. However, since the service data of the production environment is rich, the actual scene changes variously, and the performance test execution data is generally difficult to match and attach with the situation of the actual production environment in the operation process.
For example, in the same financial scenario, taking a loan as an example, the concurrency peak of the loan system is far less for period a than for period B, but the 95-line response time for period a is found to be 30% longer than for period B. Further analysis found that there was a large difference between the various types of reference values during time period a and time period B, and that the duty cycle of a service parameter was significantly greater during time period B than during time period a.
Therefore, it is needed to provide a data processing method for solving the technical problem that the test data called by the prior art is difficult to match and attach with the situation of the actual production environment in the operation process.
Disclosure of Invention
The application provides a data processing method, a device, equipment and a computer readable storage medium, which are suitable for a banking and finance system and solve the technical problem that test data called in the prior art are difficult to match and attach with the condition of an actual production environment in the operation process.
In view of this, a first aspect of the present application provides a data processing method, the method comprising:
s1, acquiring an actual production data set of a target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises time configuration and field configuration;
s2, generating a data change trend report of the target scene according to preset dimensions and time spans of actual production data contained in the actual production data set.
Optionally, the step S2 specifically includes:
and generating a change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period according to the service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
Optionally, the step S2 specifically includes:
and generating a change trend of the actual production data of different service parameter types with correlation in a second preset time period in the actual production data set according to the correlation among different service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
Optionally, the step S2 further includes:
s3, constructing a test data calling template of the target scene according to the data change trend report;
s4, calling a test data set of the target scene from a target database through the test data calling template;
s5, performing performance pressure test on the target scene based on the test data set.
A second aspect of the present application provides a data processing apparatus, the apparatus comprising:
the acquisition unit is used for acquiring an actual production data set of the target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises a time configuration and a field configuration;
and the processing unit is used for generating a data change trend report of the target scene according to the preset dimension and time span of the actual production data contained in the actual production data set.
Optionally, the processing unit is specifically configured to:
and generating a change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period according to the service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
Optionally, the processing unit is specifically configured to:
and generating a change trend of the actual production data of different service parameter types with correlation in a second preset time period in the actual production data set according to the correlation among different service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
Optionally, the method further comprises:
the construction unit is used for constructing a test data calling template of the target scene according to the data change trend report;
the calling unit is used for calling the test data set of the target scene from the target database through the test data calling template;
and the testing unit is used for performing performance pressure testing on the target scene based on the testing data set.
A third aspect of the application provides a data processing apparatus, the apparatus comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the steps of the method of data processing as described in the first aspect above, according to instructions in the program code.
A fourth aspect of the application provides a computer readable storage medium for storing program code for performing the method of the first aspect described above.
From the above technical solutions, the embodiment of the present application has the following advantages:
the application provides a data processing method, a device, equipment and a computer readable storage medium, wherein a real production data set is formed by configuring time and fields in a target scene and collecting required real production data, the change trend of the real production data with different preset dimensions and time spans in the real production data set is analyzed, a data change trend report of the target scene is formed, the analysis time of test data required by the target scene is saved, the performance test efficiency of the target scene is improved, meanwhile, the preset dimensions can be adaptively adjusted according to the actual situation, the use is convenient, and the technical problem that the test data called in the prior art are difficult to match and attach with the conditions of the actual production environment in the operation process is solved.
Drawings
FIG. 1 is a flow chart of a first method of data processing in an embodiment of the present application;
FIG. 2 is a flow chart of a second method of data processing method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a first configuration of a data processing apparatus according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a second configuration of a data processing apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make the present application better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The application designs a data processing method, a device, equipment and a computer readable storage medium, which solve the technical problem that test data called in the prior art are difficult to match and attach with the conditions of the actual production environment in the operation process.
For ease of understanding, referring to fig. 1, fig. 1 is a flowchart of a first method of data processing method according to an embodiment of the present application, as shown in fig. 1, specifically:
s1, acquiring an actual production data set of a target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises time configuration and field configuration;
it should be noted that, during the actual running process of the target financial business scenario, different actual production financial data are correspondingly generated, but not all the actual production financial data are required for the performance pressure test of the target financial business scenario, for example, in the loan business process, the actual production financial data include but are not limited to: the same actual production financial data can be divided into a plurality of types according to fields, wherein, when the performance pressure test is carried out on the loan business system of the bank, the loan approval data can not be used as the data required by the performance pressure test of the target financial business scene.
Thus, the target field and the target time may be configured by a preset acquisition configuration.
The target fields may include, but are not limited to: transaction type, transaction channel, transaction party, transaction amount, transaction institution, etc.;
the target time may be a periodic period of time, such as 15 to 18 points per day, or a fixed period of time, such as 24 hours within an exact date.
The current data acquisition mode has higher flexibility, and can be adaptively adjusted according to actual conditions.
S2, generating a data change trend report of the target scene according to preset dimensionality and time span of actual production data contained in the actual production data set;
it should be noted that, for the collected and obtained target time and the actual production data set of the target field where the actual production data is located, the data change trend of the actual production data in the actual production data set can be analyzed through the setting of different preset dimensions, so as to form a data change trend report of the target scene, and provide a basis for the test data of the performance pressure test of the target scene. For example, actual production data for four different transaction types for scenario a varies in terms of different duty cycles over the past month. The data change trend report is very helpful to the stability of the actual performance test and the selection of the service data of the mixed scene of the performance test, and can be well attached to the peak condition of the actual production environment.
The step S2 specifically includes:
according to the service parameter types of the actual production data contained in the actual production data set, generating the change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period, and obtaining a data change trend report of a target scene.
It should be noted that a single service parameter type may be selected as a preset dimension to generate a variation trend of actual production data of different single service parameter types within a first preset time period, so as to analyze a service parameter type having a great influence on a performance pressure test of a target scene in a long term or a short term, or analyze a situation of determining peaks and troughs of different service parameter types, for example, generate a data variation trend of a transaction amount ratio under different transaction channels according to the transaction channels.
Further, step S2 may further include:
according to the correlation among different business parameter types of the actual production data contained in the actual production data set, generating the change trend of the actual production data of different business parameter types with correlation in a second preset time period in the actual production data set, and obtaining a data change trend report of a target scene.
It should be noted that, in the performance pressure test of the actual target scenario, it is sometimes difficult for a single service parameter type to meet the actual requirement, so further, by analyzing the correlation between different service parameter types, a trend of the actual production data of the different service parameter types with the correlation is generated, so as to determine the different service parameter types required by the test data of the target scenario.
Referring to fig. 2, fig. 2 is a flowchart showing a second method of data processing method according to the embodiment of the present application, as shown in fig. 2, specifically:
s3, constructing a test data calling template of the target scene according to the data change trend report;
it should be noted that, according to the data change trend report, the test data call template used for constructing the target scene is constructed, for example, the time from the beginning of the rising trend presentation in the data change trend report is taken as a starting point, the time from the passing of one peak to the next beginning of the rising trend presentation is taken as an ending point, so as to determine the service parameter type, the time period, the data volume and the like of the test data, and construct the test data call template.
S4, calling a test data set of the target scene from the target database through a test data calling template;
when the pressure test is required to be performed on the target scene, the test data set of the target scene is called according to the time point of the test.
And S5, performing performance pressure test on the target scene based on the test data set.
Referring to fig. 3, fig. 3 is a schematic diagram of a first structure of a data processing apparatus according to an embodiment of the present application, as shown in fig. 3, specifically including:
an obtaining unit 301, configured to obtain an actual production dataset of a target scene under a preset acquisition configuration, where the preset acquisition configuration includes a time configuration and a field configuration;
the processing unit 302 is configured to generate a data change trend report of the target scenario according to a preset dimension and a time span of actual production data included in the actual production data set.
Further, the processing unit 302 is specifically configured to:
according to the service parameter types of the actual production data contained in the actual production data set, generating the change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period, and obtaining a data change trend report of a target scene.
Further, the processing unit 302 is specifically configured to:
according to the correlation among different business parameter types of the actual production data contained in the actual production data set, generating the change trend of the actual production data of different business parameter types with correlation in a second preset time period in the actual production data set, and obtaining a data change trend report of a target scene.
Further, referring to fig. 4, fig. 4 is a schematic diagram of a second structure of the data processing apparatus according to the third embodiment of the present application, as shown in fig. 4, further including:
a construction unit 401, configured to construct a test data call template of the target scene according to the data change trend report;
a calling unit 402, configured to call a test data set of the target scene from the target database through a test data call template;
and a test unit 403, configured to perform performance pressure test on the target scenario based on the test data set.
The embodiment of the present application further provides another data processing apparatus, as shown in fig. 5, for convenience of explanation, only the portion relevant to the embodiment of the present application is shown, and specific technical details are not disclosed, please refer to the method portion of the embodiment of the present application. The terminal can be any terminal equipment including a mobile phone, a tablet personal computer, a personal digital assistant (English full name: personal DigitalAssistant, english abbreviation: PDA), a sales terminal (English full name: point of sales, english abbreviation: POS), a vehicle-mounted computer and the like, taking the mobile phone as an example of the terminal:
fig. 5 is a block diagram showing a part of a structure of a mobile phone related to a terminal provided by an embodiment of the present application. Referring to fig. 5, the mobile phone includes: radio Frequency (RF) circuit 1010, memory 1020, input unit 1030, display unit 1040, sensor 1050, audio circuit 1060, wireless fidelity (wireless fidelity, wiFi) module 1070, processor 1080, and power source 1090. Those skilled in the art will appreciate that the handset configuration shown in fig. 5 is not limiting of the handset and may include more or fewer components than shown, or may combine certain components, or may be arranged in a different arrangement of components.
The following describes the components of the mobile phone in detail with reference to fig. 5:
the RF circuit 1010 may be used for receiving and transmitting signals during a message or a call, and particularly, after receiving downlink information of a base station, the signal is processed by the processor 1080; in addition, the data of the design uplink is sent to the base station. Generally, RF circuitry 1010 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (English full name: lowNoiseAmplifier, english abbreviation: LNA), a duplexer, and the like. In addition, the RF circuitry 1010 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol, including but not limited to global system for mobile communications (english: global System ofMobile communication, english: GSM), general packet radio service (english: generalPacket Radio Service, GPRS), code division multiple access (english: code Division Multiple Access, english: CDMA), wideband code division multiple access (english: wideband Code DivisionMultipleAccess, english: WCDMA), long term evolution (english: long TermEvolution, english: LTE), email, short message service (english: shortMessaging Service, SMS), and the like.
The memory 1020 may be used to store software programs and modules that the processor 1080 performs various functional applications and data processing of the handset by executing the software programs and modules stored in the memory 1020. The memory 1020 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, memory 1020 may include high-speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state memory device.
The input unit 1030 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the handset. In particular, the input unit 1030 may include a touch panel 1031 and other input devices 1032. The touch panel 1031, also referred to as a touch screen, may collect touch operations thereon or thereabout by a user (e.g., operations of the user on the touch panel 1031 or thereabout using any suitable object or accessory such as a finger, stylus, etc.), and drive the corresponding connection device according to a predetermined program. Alternatively, the touch panel 1031 may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch azimuth of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device and converts it into touch point coordinates, which are then sent to the processor 1080 and can receive commands from the processor 1080 and execute them. Further, the touch panel 1031 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. The input unit 1030 may include other input devices 1032 in addition to the touch panel 1031. In particular, other input devices 1032 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a track ball, a mouse, a joystick, etc.
The display unit 1040 may be used to display information input by a user or information provided to the user and various menus of the mobile phone. The display unit 1040 may include a display panel 1041, and alternatively, the display panel 1041 may be configured in the form of a liquid crystal display (english full name: liquid Crystal Display, acronym: LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch panel 1031 may overlay the display panel 1041, and when the touch panel 1031 detects a touch operation thereon or thereabout, the touch panel is transferred to the processor 1080 to determine a type of touch event, and then the processor 1080 provides a corresponding visual output on the display panel 1041 according to the type of touch event. Although in fig. 5, the touch panel 1031 and the display panel 1041 are two independent components for implementing the input and output functions of the mobile phone, in some embodiments, the touch panel 1031 and the display panel 1041 may be integrated to implement the input and output functions of the mobile phone.
The handset may also include at least one sensor 1050, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 1041 according to the brightness of ambient light, and the proximity sensor may turn off the display panel 1041 and/or the backlight when the mobile phone moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the acceleration in all directions (generally three axes), and can detect the gravity and direction when stationary, and can be used for applications of recognizing the gesture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer and knocking), and the like; other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc. that may also be configured with the handset are not described in detail herein.
Audio circuitry 1060, a speaker 1061, and a microphone 1062 may provide an audio interface between a user and a cell phone. Audio circuit 1060 may transmit the received electrical signal after audio data conversion to speaker 1061 for conversion by speaker 1061 into an audio signal output; on the other hand, microphone 1062 converts the collected sound signals into electrical signals, which are received by audio circuit 1060 and converted into audio data, which are processed by audio data output processor 1080 for transmission to, for example, another cell phone via RF circuit 1010 or for output to memory 1020 for further processing.
WiFi belongs to a short-distance wireless transmission technology, and a mobile phone can help a user to send and receive emails, browse webpages, access streaming media and the like through a WiFi module 1070, so that wireless broadband Internet access is provided for the user. Although fig. 5 shows a WiFi module 1070, it is understood that it does not belong to the necessary constitution of the handset, and can be omitted entirely as required within the scope of not changing the essence of the application.
Processor 1080 is the control center of the handset, connects the various parts of the entire handset using various interfaces and lines, and performs various functions and processes of the handset by running or executing software programs and/or modules stored in memory 1020, and invoking data stored in memory 1020, thereby performing overall monitoring of the handset. Optionally, processor 1080 may include one or more processing units; preferably, processor 1080 may integrate an application processor primarily handling operating systems, user interfaces, applications, etc., with a modem processor primarily handling wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 1080.
The handset further includes a power source 1090 (e.g., a battery) for powering the various components, which may preferably be logically connected to the processor 1080 by a power management system, such as to provide for managing charging, discharging, and power consumption by the power management system.
Although not shown, the mobile phone may further include a camera, a bluetooth module, etc., which will not be described herein.
In an embodiment of the present application, the processor 1080 included in the terminal further has the following functions:
s1, acquiring an actual production data set of a target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises time configuration and field configuration;
s2, generating a data change trend report of the target scene according to the preset dimension and time span of the actual production data contained in the actual production data set.
Further, step S2 further includes:
s3, constructing a test data calling template of the target scene according to the data change trend report;
s4, calling a test data set of the target scene from the target database through a test data calling template;
and S5, performing performance pressure test on the target scene based on the test data set.
The embodiments of the present application also provide a computer readable storage medium storing a program code for executing any one of the data processing methods described in the foregoing embodiments.
In the embodiment of the application, a data processing method, a device, equipment and a computer readable storage medium are provided, a real production data set is formed by configuring time and fields in a target scene and collecting required real production data, the change trends of the real production data of different preset dimensions and time spans in the real production data set are analyzed, a data change trend report of the target scene is formed, the analysis time of test data required by the target scene is saved, the performance test efficiency of the target scene is improved, meanwhile, the preset dimensions can be adaptively adjusted according to the actual situation, the use is convenient, and the technical problems that the test data called in the prior art are difficult to match and attach with the conditions of the actual production environment in the operation process are solved.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The terms "first," "second," "third," "fourth," and the like in the description of the application and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "and/or" for describing the association relationship of the association object, the representation may have three relationships, for example, "a and/or B" may represent: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, mobile hard disk, read-Only Memory (ROM), random access Memory (RandomAccess Memory, RAM), magnetic disk or optical disk, etc.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A method of data processing, comprising:
s1, acquiring an actual production data set of a target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises time configuration and field configuration;
s2, generating a data change trend report of the target scene according to preset dimensions and time spans of actual production data contained in the actual production data set.
2. The data processing method according to claim 1, wherein the step S2 specifically includes:
and generating a change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period according to the service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
3. The data processing method according to claim 1, wherein the step S2 specifically includes:
and generating a change trend of the actual production data of different service parameter types with correlation in a second preset time period in the actual production data set according to the correlation among different service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
4. The data processing method according to claim 1, wherein after the step S2, further comprises:
s3, constructing a test data calling template of the target scene according to the data change trend report;
s4, calling a test data set of the target scene from a target database through the test data calling template;
s5, performing performance pressure test on the target scene based on the test data set.
5. A data processing apparatus, comprising:
the acquisition unit is used for acquiring an actual production data set of the target scene under a preset acquisition configuration, wherein the preset acquisition configuration comprises a time configuration and a field configuration;
and the processing unit is used for generating a data change trend report of the target scene according to the preset dimension and time span of the actual production data contained in the actual production data set.
6. The data processing device according to claim 5, wherein the processing unit is specifically configured to:
and generating a change trend of the actual production data of different service parameter types in the actual production data set within a first preset time period according to the service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
7. The data processing device according to claim 5, wherein the processing unit is specifically configured to:
and generating a change trend of the actual production data of different service parameter types with correlation in a second preset time period in the actual production data set according to the correlation among different service parameter types of the actual production data contained in the actual production data set, and obtaining a data change trend report of the target scene.
8. The data processing apparatus of claim 5, further comprising:
the construction unit is used for constructing a test data calling template of the target scene according to the data change trend report;
the calling unit is used for calling the test data set of the target scene from the target database through the test data calling template;
and the testing unit is used for performing performance pressure testing on the target scene based on the testing data set.
9. A data processing apparatus, the apparatus comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the data processing method of any of claims 1-4 according to instructions in the program code.
10. A computer readable storage medium, characterized in that the computer readable storage medium is for storing a program code for performing the data processing method of any one of claims 1-4.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310719315.0A CN116680188A (en) | 2023-06-16 | 2023-06-16 | Data processing method, device, equipment and computer readable storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310719315.0A CN116680188A (en) | 2023-06-16 | 2023-06-16 | Data processing method, device, equipment and computer readable storage medium |
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| CN116680188A true CN116680188A (en) | 2023-09-01 |
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| CN202310719315.0A Pending CN116680188A (en) | 2023-06-16 | 2023-06-16 | Data processing method, device, equipment and computer readable storage medium |
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| CN (1) | CN116680188A (en) |
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