CN107329881B - Application system performance test method and device, computer equipment and storage medium - Google Patents
Application system performance test method and device, computer equipment and storage medium Download PDFInfo
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- CN107329881B CN107329881B CN201710409330.XA CN201710409330A CN107329881B CN 107329881 B CN107329881 B CN 107329881B CN 201710409330 A CN201710409330 A CN 201710409330A CN 107329881 B CN107329881 B CN 107329881B
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Abstract
A method and device for testing application system performance, computer equipment and storage medium include: acquiring a current first performance parameter; determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and a fitting function; when the second performance parameter does not belong to a first preset range, updating the first performance parameter according to the first preset range and the fitting function; when the second performance parameter belongs to a first preset range, acquiring a third performance parameter corresponding to the first performance parameter; if the third performance parameter belongs to a second preset range, recording a test result; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter. The testing method and device, the computer equipment and the storage medium can test the performance of the application system without repeatedly adjusting according to experience by a test engineer, and the efficiency is higher than that of a manual testing mode.
Description
Technical Field
The present invention relates to the field of computer testing technologies, and in particular, to a method and an apparatus for testing performance of an application system, a computer device, and a storage medium.
Background
In a C/S (client/server) model based application system, a client sends a request to a server, and the server calculates a correlation result according to a certain algorithm and returns the correlation result to the client. The main bottleneck of the application system is in the cpu of the server, and as tps (transactionapsecond, transaction number/second) increases, the cpu utilization of the server increases, and the time consumption of each request increases, so that the timeout rate corresponding to a specific timeout threshold increases continuously, and further, the error rate increases continuously. An excessively high error rate affects the effect of the application system, cannot be tolerated by the client, and normally, the cpu utilization rate of the production environment needs to be kept at a reasonable level due to factors such as disaster tolerance, peak traffic handling and the like. Therefore, the performance test result can be tps when the error rate and the cpu utilization rate of the application system satisfy a certain condition. For example, a typical test scenario is to set the timeout threshold of the error caused by timeout to 20ms (milliseconds), which requires that the test application system tps under the condition that the error rate per minute is not higher than one thousandth and the cpu usage is not higher than 70%.
The traditional application system performance testing method is mainly a manual testing method, pressure load tps is configured through a client configuration page, pressure testing is conducted for a period of time (for example, 5 minutes), indexes such as an error rate and a cpu utilization rate under the load are obtained through a third-party system (for example, a monitoring system), if the current error rate or the cpu utilization rate does not meet the performance standard, the client load tps is continuously adjusted according to experience, then whether a testing result meets a condition is confirmed, and the process is continuously iterated until a proper tps is adjusted to meet the performance testing standard. Because the traditional application system testing method is manual testing and needs to be adjusted repeatedly according to experience, the testing efficiency is low.
Disclosure of Invention
In view of the above, it is necessary to provide an application system testing method and apparatus, a computer device, and a storage medium, which improve testing efficiency, for solving the problem of low testing efficiency.
An application system performance testing method comprises the following steps:
acquiring a current first performance parameter;
determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and a fitting function; the fitting function is a curve function of the second performance parameter with respect to the first performance parameter;
when the second performance parameter does not belong to a first preset range, updating the first performance parameter according to the first preset range and the fitting function;
when the second performance parameter belongs to a first preset range, acquiring a third performance parameter corresponding to the first performance parameter; before the application system reaches a performance bottleneck, the second performance parameter and the third performance parameter increase as the first performance parameter increases;
if the third performance parameter belongs to a second preset range, recording a test result; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter.
An application system performance testing device, comprising:
the current value acquisition module is used for acquiring a current first performance parameter;
the first parameter acquisition module is used for determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and the fitting function; the fitting function is a curve function of the second performance parameter with respect to the first performance parameter;
the parameter updating module is used for updating the first performance parameter according to the first preset range and the fitting function when the second performance parameter does not belong to the first preset range;
the second parameter acquisition module is used for acquiring a third performance parameter corresponding to the first performance parameter when the second performance parameter belongs to a first preset range; before the application system reaches a performance bottleneck, the second performance parameter and the third performance parameter increase as the first performance parameter increases;
the result recording module is used for recording a test result if the third performance parameter belongs to a second preset range; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the application system performance testing method as claimed above when executing the computer program.
A computer storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the steps of the application system performance testing method described above.
The testing method and device, the computer equipment and the storage medium can test the performance of the application system without repeatedly adjusting according to experience by a test engineer, and the efficiency is higher than that of a manual testing mode.
Drawings
FIG. 1 is a schematic diagram of an application environment of a method and an apparatus for testing performance of an application system according to an embodiment;
FIG. 2 is a schematic diagram of the internal structure of the server of FIG. 1;
FIG. 3 is a flow chart of a method for testing performance of an application system according to an embodiment;
FIG. 4 is a graph of performance between tps and cpu usage for one embodiment;
FIG. 5 is a graph of performance between tps and error rate for one embodiment;
FIG. 6 is a flowchart of an application system performance testing method according to another embodiment;
FIG. 7 is a detailed flow chart of one step of the application system performance testing method of FIG. 6;
FIG. 8 is a block diagram of an embodiment of an application system performance testing apparatus;
FIG. 9 is a block diagram of an application system performance testing apparatus according to another embodiment;
fig. 10 is a detailed block diagram of one block of the application system performance testing apparatus of fig. 9.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a schematic application environment diagram of an application system performance testing method for improving performance testing efficiency according to an embodiment. As shown in fig. 1, the application environment includes a client 110, a network 120, and a server 130, and the client 110 and the server 130 are connected through the network 120. Client 110 runs a client program of an application system and sends a request to server 130 via network 120. The client 110 may be a mobile phone, a tablet computer, a personal digital assistant, a wearable device, or the like. The server 130 runs the server program of the application system and returns the result to the client 110. In this embodiment, the application system performance test method is run in the server 130. In other application scenarios, only server 130 may be included.
Fig. 2 is a schematic diagram of the internal structure of the server 130 in one embodiment. As shown in fig. 2, the server 130 includes a processor, a storage medium, an internal memory, a network interface, and an input device connected through a system bus. The storage medium of the server 130 stores an operating system and a computer application program of an application system performance testing apparatus, and when the computer application program of the application system performance testing apparatus is executed by a processor, the application system performance testing method is implemented. The processor is used to provide computational and control capabilities to support the operation of the entire server 130. The internal memory of the server 130 provides an environment for the application system performance testing apparatus in the storage medium to operate, and the internal memory may store computer readable instructions, and when the computer readable instructions are executed by the processor, the processor may be caused to execute an application system performance testing method. The network interface of the server 130 is used for network communication with the client 110, such as receiving a request sent by the client 110 through the network 120. The display screen of the server 130 may be a liquid crystal display screen or an electronic ink display screen, and the input device may be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a housing of the user terminal, or an external keyboard, a touch pad or a mouse. Those skilled in the art will appreciate that the architecture shown in fig. 2 is a block diagram of only a portion of the architecture associated with the inventive arrangements and is not intended to limit the servers to which the inventive arrangements may be applied, and that a particular server may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Referring to fig. 3, in one embodiment, a performance testing method is provided, which is executed in the server 130 shown in fig. 1, and includes the following steps:
s310: and acquiring a current first performance parameter.
The performance parameters are parameters capable of characterizing the performance condition of the application system. Such as tps, cpu usage of the application system, error rate, timeout rate, memory usage, disk usage, network bandwidth, etc. The first performance parameter is a performance parameter, and may be any one of tps, cpu usage of an application system, error rate, timeout rate, memory usage, disk usage, and network bandwidth. In one implementation, the first performance parameter is tps.
Wherein tps is an abbreviation of transactispersesecond, i.e., transaction number/second, which represents the number of transactions per second processed by the application system, and is a performance index for measuring the processing capacity of the application system. A transaction is a process in which a client sends a request to a server and the server reacts. In one embodiment, the transaction may refer to a process in which the client sends a request to an application system (e.g., an advertisement recommendation system), and the application system calculates a correlation result according to an algorithm and returns the correlation result to the client. It should be noted that tps is generally an index under the constraint conditions of a certain application system resource (cpu utilization rate, memory utilization rate, etc.) and error rate (or timeout rate).
The cpu utilization, which indicates how much cpu resources are occupied by the application system at a time point or in a time period, can be represented by the proportion of the cpu resources occupied by the application system. In one embodiment, cpu usage may be represented by an average of the cpu resource usage over a period of time (e.g., 5 minutes).
The error rate and the timeout rate respectively represent the proportion of the number of the transactions which are in error and timeout of the application system in the total number of the transactions within a period of time. In one embodiment, the error rate and the timeout rate may be represented by an average of the number of transactions that have failed within a period of time and the number of transactions that have timed out to the total number of transactions within the period of time, respectively.
The memory utilization rate, the disk utilization rate and the network bandwidth respectively represent the amount of memory resources, disk resources and network resources occupied by the application system at a certain time point or within a certain period of time. In a specific embodiment, the average value of the proportion of the application system occupying the whole memory resource, the disk resource and the network resource of the server is used for representing the average value.
S330: determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and the fitting function; the fitting function is a curve function of the second performance parameter with respect to the first performance parameter.
The second performance parameter is a performance parameter different from the first performance parameter, and may be any one of tps, cpu usage of an application system, an error rate, a timeout rate, memory usage, disk usage, and network bandwidth, which is different from the first performance parameter. In one implementation, the second performance parameter is cpu usage.
The fitting function may be a fitting function obtained by curve fitting according to the second performance parameter and the historical data of the first performance parameter. Curve fitting is a data processing method that approximately describes or mimics the functional relationship between coordinates represented by discrete groups of points on a plane with a continuous curve. It should be noted that, when the historical data of the first performance parameter and the second performance parameter is empty or less than the preset number, the fitting function may be set as a preset function.
The second performance parameter can be quickly acquired by determining the second performance parameter corresponding to the first performance parameter through the fitting function, and the testing efficiency is improved to a certain extent.
S340: and when the second performance parameter does not belong to the first preset range, updating the first performance parameter according to the first preset range and the fitting function.
And when the second performance parameter does not belong to the first preset range, the value of the first performance parameter is not in the range before the performance of the application system reaches the bottleneck. Therefore, it is necessary to determine the first performance parameter in the range before the performance of the application system reaches the bottleneck according to the first preset range and the fitting function. In a preferred embodiment, after updating the first performance parameter, the method returns to step S310.
S350: and when the second performance parameter belongs to the first preset range, acquiring a third performance parameter corresponding to the first performance parameter. The second performance parameter and the third performance parameter increase as the first performance parameter increases before the application system reaches the performance bottleneck.
The first predetermined range is a fluctuation range of the second performance parameter before the performance of the application system reaches the bottleneck. Optionally, the first preset range may be: is not greater than the first threshold value and is not less than the difference between the first threshold value and the first preset fluctuation value. The first threshold is a value of the second performance parameter when the application system reaches the bottleneck. Since the performance parameter may have slight differences in the test results at different time periods, and may not be completely equal to a fixed value, the fluctuation is allowed within a certain range, and in the present embodiment, the maximum fluctuation value allowed by the second performance parameter is represented by the first preset fluctuation value. In one particular embodiment, the method may be performed by: C-C < ═ second performance parameter < ═ C to indicate that the second performance parameter falls within a first preset range. Where C represents a first threshold value and C represents a first preset fluctuation value.
In this embodiment, the first performance parameter, the second performance parameter, and the third performance parameter need to satisfy the following requirements: the second performance parameter and the third performance parameter increase as the first performance parameter increases before the application system reaches the performance bottleneck. The performance bottleneck is actually a performance deficiency of an application system. The performance bottleneck on hardware mainly refers to problems in terms of cpu, memory and the like. For example, when software requirement analysis and summary design are performed, it is determined that 6 CPUs and 12G memories are required on a database server, but when the CPU utilization rate exceeds 95% continuously during testing, it can be considered that a performance bottleneck occurs on hardware.
S370: and if the third performance parameter belongs to the second preset range, recording the test result. The test result comprises a first performance parameter, a second performance parameter and a third performance parameter.
And when the third performance parameter belongs to a second preset range, recording the first performance parameter, the second performance parameter and the third performance parameter at the moment as a corresponding performance test result under the condition of the current first performance parameter.
The second preset range is a range of the third performance parameter before the performance of the application system reaches the bottleneck. Optionally, the second preset range is not greater than the second threshold. The second threshold is a value of the third performance parameter when the application system reaches the bottleneck. In one particular embodiment, one may use: and the error rate < ═ E indicates that the third performance parameter belongs to a second preset range, wherein E indicates a second threshold value.
In a preferred embodiment, the first predetermined range is not greater than the first threshold and not less than the difference between the first threshold and the first predetermined fluctuation value; the second predetermined range is not greater than a second threshold.
According to the application system performance testing method, the performance of the application system can be tested without repeated adjustment of a test engineer according to experience, and the efficiency is higher than that of a manual testing mode.
Further, when the second performance parameter does not belong to the first preset range, the first performance parameter may be updated according to the fitting function and a maximum value, a minimum value, or an average value of the first preset range. That is, the maximum value, the minimum value, or the average value of the first preset range may be substituted into the fitting function to update the first performance parameter. It will be appreciated that the first performance parameter may also be updated based on the fitting function and other values of the first predetermined range. In this embodiment, after the step of recording the test result, i.e. after step S370, the method further includes: and updating the fitting function according to the test result.
Through a number of experiments and observations, a performance curve between tps and cpu usage can be obtained as shown in fig. 4. As tps increases, cpu usage goes from 0 (actually slightly greater than 0 because the operating system itself has system overhead) to 100% (actually may not reach 100% because the application may initiate an anti-avalanche mechanism under extreme tps loading, with partial transaction requests being rejected, thereby reducing cpu usage). Repeated experiments show that in a proper load range, such as before an application system reaches a performance bottleneck, a binomial function curve can be well fitted between the CPU utilization rate and tps. It should be noted that the more data pairs are sampled during the fitting process, the more accurate the fitted function is.
the performance curve between tps and error rate is shown in figure 5. When Tps is between 0 and Tps2, the application program will not substantially be in error due to the low cpu utilization. These errors are mainly timeout errors due to request timeouts. As tps continues to increase, cpu usage continues to increase, and error rates increase, until the error rate reaches 100%.
As can be seen from fig. 4 and 5, the second performance parameter and the first performance parameter have a better linear relationship before the application system reaches the performance bottleneck. Thus, in a preferred embodiment, the first performance parameter may be tps, the second performance parameter may be cpu usage, and the third performance parameter may be error rate.
In one embodiment, the first performance parameter is tps, the second performance parameter is cpu utilization, and the third performance parameter is error rate. The test results can be saved using list, and the format for saving the single test results is: [ tps, cpu _ load, error _ rate ], which in turn represents tps, cpu usage and error rate. Storing the result of each test according to the execution sequence to obtain a test result list, wherein the format of the test result list can be as follows: test _ result _ list [ [ tps1, cpu _ load1, error _ rate1], [ tps2, cpu _ load2, error _ rate2], … … ]. After the test is completed every time tps is changed, the corresponding test result may be added to test _ result _ list.
In this particular embodiment, the fitting function may be defined as: the tps and the cpu usage satisfy a binomial function (may be simply referred to as a QC function) of y ═ a × x + b × x + c. Where y represents cpu _ load, i.e., cpu usage; x represents tps. To determine the parameters a and b, a curve fit can be made based on a history of tps tested and a history of cpu usage. The function of curve fitting can be realized by defining a curve fitting function curve _ fit (x _ list, y _ list), so as to obtain a fitting function. The parameters x _ list and y _ list can be respectively substituted by corresponding elements in the tps _ list and the cpu _ load _ list, so that the QC function is determined. Wherein tps _ list is a list consisting of tps for each test, and can be obtained by [ i [0] for i in test _ result _ list ]; the cpu _ load _ list is a list consisting of cpu utilization rates of each test; can be obtained by cpu _ load _ list ═ i [1] for i in test _ result _ list ]. The curve fitting function curr _ fit may return a QC function determined by a, b. Further, after the QC function performs one test after changing tps each time, the QC function may perform refitting according to the latest test _ result _ list, and the refitted QC function is used for next tps or cpu usage evaluation (determining cpu usage to solve tps or vice versa).
Referring to fig. 6, in one embodiment, the method further includes:
s381: and if the third performance parameter does not belong to the second preset range, acquiring a preset updating step length of the second performance parameter.
If the third performance parameter does not belong to the second preset range, the current third performance parameter is within a range after the performance of the application system reaches the bottleneck, that is, the current third performance parameter is larger, and at this time, the first performance parameter can be reduced by reducing the second performance parameter, so that the third performance parameter is reduced.
S383: and updating the second performance parameter according to a value obtained by subtracting the preset updating step length from the second performance parameter, and updating the first performance parameter according to the updated second performance parameter and the fitting function.
In this embodiment, the first performance parameter is reduced by reducing the second performance parameter by subtracting the preset update step size from the second performance parameter.
S385: and acquiring a third performance parameter corresponding to the first performance parameter.
Since the obtained first performance parameter is updated, that is, the first performance parameter after being reduced, the corresponding third performance parameter is necessarily reduced relative to the third performance parameter before being updated.
S387: and recording the test result when the third performance parameter belongs to a third preset range.
The third predetermined range is within the second predetermined range. The third predetermined range is a fluctuation range of the third performance parameter before the performance of the application system reaches the bottleneck. Optionally, the third preset range is not less than the second threshold minus the second preset fluctuation value and not greater than the second threshold. For the same reason as the first preset fluctuation value, in the present embodiment, the maximum fluctuation value allowed for the third performance parameter is represented by the second preset fluctuation value.
In one embodiment, after the step of obtaining the third performance parameter corresponding to the first performance parameter, that is, after step S385, the method further includes:
s3861: and if the third performance parameter does not belong to the third preset range and the third performance parameter does not belong to the second preset range, returning to the step of updating the second performance parameter according to a value obtained by subtracting the preset updating step length from the second performance parameter.
Since the third predetermined range is within the second predetermined range, when the third performance parameter does not belong to the third predetermined range, the third performance parameter may belong to the second predetermined range or may not belong to the second predetermined range.
If the current third performance parameter still does not belong to the second preset range, the current third performance parameter still is within a range after the performance of the application system reaches the bottleneck, that is, the current third performance parameter is still large, at this time, the first performance parameter needs to be reduced by reducing the second performance parameter, so that the third performance parameter is reduced. Therefore, the step of updating the second performance parameter according to the value obtained by subtracting the preset updating step size from the second performance parameter, i.e. step S383, is returned.
In one embodiment, after the step of obtaining the third performance parameter corresponding to the first performance parameter, that is, after step S385, the method further includes:
s3865: and if the third performance parameter belongs to a second preset range, iteratively updating the first performance parameter corresponding to the second performance parameter by adopting a bisection method according to the historical data of the second performance parameter until the third performance parameter corresponding to the first performance parameter belongs to the third preset range, and recording a test result.
If the current third performance parameter belongs to the second preset range, the current third performance parameter is in a range before the performance of the application system reaches the bottleneck, but is not in the allowable fluctuation range. The first performance parameter corresponding to the second performance parameter can be iteratively updated by adopting a bisection method on the historical data of the second performance parameter, so that the third performance parameter corresponding to the first performance parameter belongs to a third preset range. And recording the test result until the third performance parameter belongs to a third preset range.
In this embodiment, the first preset range is not greater than the first threshold and is not less than the difference between the first threshold and the first preset fluctuation value; the second preset range is not greater than a second threshold value; the third preset range is not less than the difference of the second threshold minus the second preset fluctuation value and not greater than the second threshold. In this way, the first performance parameter corresponding to the second performance parameter can be iteratively updated by adopting the bisection method.
Therefore, the first performance parameter can be quickly converged to the corresponding third performance parameter belonging to the third preset range in the dichotomy iterative updating mode. Thus, the efficiency of the performance test is further improved.
Referring to fig. 7, in an embodiment, if the third performance parameter belongs to the second preset range, the step of iteratively updating the first performance parameter corresponding to the second performance parameter by bisection according to the historical data of the second performance parameter until the third performance parameter corresponding to the first performance parameter belongs to the third preset range, that is, the step S3865, includes:
s781: and taking the last-but-one-time data in the historical data of the second performance parameter as an upper limit and the last-but-one-time data as a lower limit.
The first preset range is not greater than the first threshold and not less than the difference between the first threshold and the first preset fluctuation value; the second preset range is not greater than a second threshold value; the third preset range is not less than the difference of the second threshold minus the second preset fluctuation value and not greater than the second threshold. Therefore, the last-but-one data in the history data of the second performance parameter is larger than the second threshold, and the last-but-one data is smaller than the difference of the second threshold minus the second preset fluctuation value. Therefore, the second-to-last data may be an upper limit and the first-to-last data may be a lower limit.
S783: and determining a median value according to the upper limit and the lower limit, and updating the first performance parameter according to the median value and the fitting function.
Determining a median value according to the upper limit and the lower limit, thereby dividing the second performance parameter into two parts: a lower limit to a median range and a median to an upper limit.
S785: and acquiring a third performance parameter corresponding to the first performance parameter.
S787: and recording the test result when the third performance parameter belongs to a third preset range.
In this embodiment, whether the third performance parameter corresponding to the first performance parameter corresponding to the median obtained by the bisection method belongs to a third preset range or not is determined to end the iteration. And when the third performance parameter belongs to a third preset range, ending the iterative updating and recording the test result.
Referring to fig. 7, in an embodiment of the present invention, if the third performance parameter belongs to the second preset range, the step of iteratively updating the first performance parameter corresponding to the second performance parameter by a bisection method according to the historical data of the second performance parameter until the third performance parameter corresponding to the first performance parameter belongs to the third preset range, that is, the step S3865, further includes:
s788: and when the third performance parameter does not belong to the third preset range, updating the upper limit or the lower limit according to whether the third performance parameter belongs to the second preset range, returning to the step of determining the median according to the upper limit and the lower limit, and updating the first performance parameter according to the median and the fitting function.
When the third performance parameter does not belong to the third preset range, the iterative updating is required to be continued.
And if the third performance parameter does not belong to the second preset range, updating the upper limit according to the last data in the historical data of the second performance parameter, returning to the step of determining the median according to the upper limit and the lower limit, and updating the first performance parameter according to the median and the fitting function.
And if the third performance parameter belongs to a second preset range, updating a lower limit according to the last data in the historical data of the second performance parameter, returning to the step of determining a median according to the upper limit and the lower limit, and updating the first performance parameter according to the median and a fitting function.
Referring to fig. 7, in one embodiment, after the step of recording the test result, namely after the step S787, the method further includes:
s789: and updating the fitting function according to the test result.
It is understood that in other embodiments, after the step of recording the test result, as in step S370, step S387, and step S3865, the method may also include: and updating the fitting function according to the test result.
Therefore, the fitting function can be more accurate, and the accuracy of the performance test of the application system is improved.
In the following, a specific embodiment is described, in which a performance test model of an application system is defined as follows:
(1) the third performance parameter is an error rate, which is not greater than a second threshold (which may be represented by E). Can be formulated as: error rate < ═ E.
(2) The second performance parameter is cpu usage, which is not greater than the first threshold (which may be denoted by C). Can be formulated as: the cpu utilization rate < ═ C.
(3) The cpu usage is not a completely accurate constraint and may fluctuate by a first preset fluctuation value (which may be denoted by c) below a first threshold. In order to fully utilize the cpu, the cpu utilization rate is not greater than the first threshold value and is sufficiently close to the first threshold value by adjusting the magnitude of the first preset fluctuation value. Can be formulated as: and the utilization rate of C-C ═ cpu ═ C.
(4) The error rate is not a completely accurate constraint and may fluctuate by a second preset fluctuation value (which may be denoted by e) below a second threshold; in order to fully utilize the cpu, the error rate is not greater than the second threshold value and is sufficiently close to the second threshold value by adjusting the magnitude of the second preset fluctuation value. Can be formulated as: E-E < ﹦ error rate < ﹦ E.
(5) And (3) under the condition that the conditions (1) and (3) are simultaneously met, successfully exiting the test, and recording the test result at the moment, wherein the test result comprises a first performance parameter (specifically tps), a cpu utilization rate and an error rate.
(6) And (4) when the conditions (2) and (4) are met, the test is successfully exited, and the test result at the moment is recorded.
The above performance test model is further explained by a specific example. Such as defining an error rate of no more than 0.1%; the CPU utilization rate is not more than 70%; on the premise that the error rate is not more than 0.1%, allowing the cpu utilization rate to fluctuate downwards by 2%, namely the cpu utilization rate is 68% -70%, and at the moment, meeting the condition of successful exit of the test; on the premise that the cpu utilization rate is not more than 70%, the error rate is allowed to fluctuate downwards by 0.05%, namely the error rate is between 0.05% and 0.1%, and at this time, the successful test exit condition is met.
According to the performance test model, a technical scheme of the performance test is as follows, and the method is simply divided into 3 main processes:
process 1: adjusting tps to enable the error rate and the cpu utilization rate to respectively meet the conditions (1) and (3), successfully exiting the test, and recording the test result; otherwise go to procedure 2.
And (2) a process: further adjusting tps to enable the cpu utilization rate and the error rate to respectively meet the conditions (2) and (4), successfully exiting the test, and recording the test result; or the cpu usage satisfies the condition (2) but the error rate does not satisfy the condition (4), the process goes to the process 3.
And 3, process: and continuously adjusting the CPU utilization rate by using a dichotomy so as to adjust tps, further enabling the error rate to finally meet the condition (4), successfully exiting the test, and recording the test result.
It should be noted that: the first threshold value C in the condition (3) may be set based on an empirical value. According to historical data, when the CPU utilization rate meets the condition (3), the condition (1) can be generally met at the same time; and the condition (3) that the cpu utilization rate satisfies can be iterated out through curve fitting of tps and the cpu utilization rate more quickly, so that the result is tested quickly. The condition (2) is satisfied by fast iteration of curve fitting of tps and cpu utilization, and the cpu utilization is adjusted by a bisection method, so that tps can be adjusted to quickly converge to the condition (4), and a result is quickly tested.
In one embodiment, the judgment functions of the above conditions (1) to (4) can be implemented by the following judgment functions defined using python language.
Condition (1) judgment function:
def check_error_rate(error_rate):
return error_rate<＝E；
condition (2) judgment function:
def check_cpu_load(cpu_load):
return cpu_load<＝C；
condition (3) judgment function:
def check_quit_condition_cpu(cpu_load):
return cpu_load>＝C-c and cpu_load<＝C；
condition (4) judgment function:
def check_quit_condition_error_rate(error_rate):
return error_rate>＝E-e and error_rate<＝E；
in one embodiment, the steps and descriptions for the application system performance test are as follows:
process 1: acquiring tps (which can be set according to experience, such as about 100 strokes/s) of an initial value, testing the cpu utilization rate corresponding to the tps, judging whether the cpu utilization rate meets a condition (3), and if not, performing repeated fitting iteration on the tps and the cpu utilization rate until the condition (3) is met; and (3) further judging whether the condition (1) is met, if so, the test result meets the exit condition, recording the current tps, the CPU utilization rate, the error rate and other information, and ending the performance test of the round, otherwise, entering the process 2, wherein the error rate is greater than E, and the CPU utilization rate is less than C.
And (2) a process: at this time, the error rate is greater than E, tps needs to be decreased, and the error is lower than E, for this reason, each time the cpu usage rate with a value d (configurable, for example, 5%) is decreased, it may be defined that the cpu usage rate after load is decreased is a variable cpu _ load _ to _ be _ reduced, cpu _ load _ to _ be _ reduced [ -1] [1] -d, where d is a preset update step size, and test _ result _ list [ -1] [1] is the cpu usage rate of the last test result. Substituting the cpu _ load _ to _ be _ reduced into a QC function, calculating corresponding tps, testing by using the new tps to obtain a new error rate, judging whether the error rate meets a condition (4), if so, meeting an exit condition (the cpu utilization rate necessarily meets a condition (2)), otherwise, judging whether the error rate meets a condition (1), if so, indicating that the error rate is in an interval of [0, E-E ], and entering the next process; if not, the error rate is still larger than E, the cpu utilization rate needs to be continuously reduced, then the process of reducing the cpu utilization rate is repeatedly executed, tps is calculated according to the fitting function, whether the condition (4) is met or not is retested, and whether the condition (1) is met or not is judged, until the error rate meets the condition (4), the test is quitted or the error rate is in the interval of [0, E-E), and the process is entered into the process 3.
And 3, process: the error rate of the last test is in the interval of [0, E-E), and the error rate of the last test is greater than E, which can be represented by a data structure as follows:
0< ═ Test _ result _ list [ -1] [2] < ═ E-E and Test _ result _ list [ -2] [2] > E;
and repeatedly iterating tps corresponding to the cpu utilization rate through a bisection method until the error rate meets the condition (4), and exiting the test, wherein the specific steps are as follows:
1) acquiring an upper limit and a lower limit of the cpu utilization:
the cpu _ load _ upper ═ test _ result _ list [ -2] [1], and the last-but-last data in the history data of the cpu usage rate is used as an upper limit;
the cpu _ load _ lower is test _ result _ list [ -1] [1], and the last data in the history data of cpu usage is used as a lower limit.
2) Determining a median cpu _ load _ middle ═ (cpu _ load _ upper + cpu _ load _ lower)/2; substituting the median cpu _ load _ middle into a QC function to determine corresponding tps; and (4) using the tps test to verify whether the error rate of the test result meets the condition (4), if so, exiting the test, otherwise, entering the step 3).
3) Further verifying whether the error rate meets the condition (1), if yes, CPU _ load _ lower ═ test _ result _ list [ -1] [1], and updating the lower limit according to the last data in the historical data of the second performance parameter; otherwise, cpu _ load _ upper ═ test _ result _ list [ -1] [1], and the upper limit is updated according to the last data in the history data of the second performance parameter.
4) And (3) repeating the steps 2) and 3) until the test result meets the condition (4) and exiting the test.
To further illustrate the beneficial effects of the present embodiment, the efficiency of the application system performance testing method of the present embodiment is compared by averaging the system performance tests of a plurality of application systems (20 in the present test), and the comparison results are shown in table 1:
TABLE 1 comparison of efficiency of manual testing and testing of this example
| Type of test | Average tps runs | Overall test time (hours) |
| Manual testing | 6.2 | 10.5 |
| Test of the present example | 4.8 | 6.4 |
From the overall test time in table 1, the test efficiency of the embodiment is improved by 72% compared with the manual test; from the viewpoint of automation, the invention can improve the efficiency because the invention can release manual testing labor.
The invention also provides an application system performance testing device corresponding to the method. An embodiment of an apparatus for testing performance of an application system, as shown in fig. 8, includes:
a current value obtaining module 810, configured to obtain a current first performance parameter;
a first parameter obtaining module 830, configured to determine, according to the first performance parameter and the fitting function, a second performance parameter corresponding to the first performance parameter; the fitting function is a curve function of the second performance parameter with respect to the first performance parameter;
a parameter updating module 840, configured to update the first performance parameter according to the first preset range and the fitting function when the second performance parameter does not belong to the first preset range;
a second parameter obtaining module 850, configured to obtain a third performance parameter corresponding to the first performance parameter when the second performance parameter belongs to a first preset range; before the application system reaches a performance bottleneck, the second performance parameter and the third performance parameter increase as the first performance parameter increases;
the result recording module 870 is configured to record a test result if the third performance parameter belongs to a second preset range; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter.
According to the application system performance testing method, the performance of the application system can be tested without repeated adjustment of a test engineer according to experience, and the efficiency is higher than that of a manual testing mode.
Further, the parameter updating module is configured to update the first performance parameter according to the fitting function and a maximum value, a minimum value, or an average value of the first preset range when the second performance parameter does not belong to the first preset range.
Referring to fig. 9, in one embodiment, the apparatus further includes a step length obtaining module 881, an index updating module 883, and a third parameter obtaining module 885;
the step length obtaining module 881, configured to obtain a preset update step length of the second performance parameter if the third performance parameter does not belong to the second preset range;
the index updating module 883 is configured to update the second performance parameter according to a value obtained by subtracting the preset updating step length from the second performance parameter, and update the first performance parameter according to the updated second performance parameter and the fitting function;
the third parameter obtaining module 885 is configured to obtain a third performance parameter corresponding to the first performance parameter;
the result recording module 870 is further configured to record a test result when the third performance parameter belongs to a third preset range; the third preset range is within the second preset range.
In one embodiment, the method further comprises the following steps:
a range determining module 886, configured to invoke the index updating module 883 if the third performance parameter does not belong to the third preset range and the third performance parameter does not belong to the second preset range.
In one embodiment, the first preset range is not greater than a first threshold and is not less than a difference between the first threshold and a first preset fluctuation value; the second preset range is not greater than a second threshold value; the third preset range is not less than the difference obtained by subtracting a second preset fluctuation value from the second threshold value and is not greater than the second threshold value;
the result recording module 870 is further configured to, if the third performance parameter belongs to the second preset range, iteratively update the first performance parameter corresponding to the second performance parameter by a bisection method according to the historical data of the second performance parameter, and record a test result until the third performance parameter corresponding to the first performance parameter belongs to the third preset range.
Referring to fig. 10, in one embodiment, the result recording module 870 includes:
an upper and lower limit determining unit 981, configured to use the last data in the history data of the second performance parameter as an upper limit, and use the last data as a lower limit;
a median determining unit 983, configured to determine a median according to the upper limit and the lower limit, and update the first performance parameter according to the median and the fitting function;
a corresponding parameter obtaining unit 985, configured to obtain the third performance parameter corresponding to the first performance parameter;
a test result recording unit 987, configured to record a test result when the third performance parameter belongs to the third preset range.
In one embodiment, the result recording module 870 further includes:
an upper and lower limit updating unit 988, configured to update the upper limit or the lower limit according to whether the third performance parameter belongs to the second preset range, and invoke the median determining unit, when the third performance parameter does not belong to the third preset range.
In one embodiment, the method further comprises the following steps:
a fitting function updating unit 989, configured to update the fitting function according to the test result.
In other embodiments, a fitting function updating module may also be included for updating the fitting function according to the test result after the result recording module records the test result.
The invention also provides computer equipment and a computer storage medium which correspond to the method one by one.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the application system performance testing method as described in any one of the above when executing the computer program.
The computer equipment can test the performance of the application system without being repeatedly adjusted by a test engineer according to experience, and the efficiency of the computer equipment is higher than that of a manual test mode.
The invention also provides a computer storage medium, wherein a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the steps of the application system performance testing method are realized.
The storage medium can test the performance of the application system without being repeatedly adjusted by a test engineer according to experience, and the efficiency of the storage medium is higher than that of a manual test mode.
Since the above-mentioned application system performance testing device and the above-mentioned application system performance testing method correspond to each other, detailed description of specific technical features in the device corresponding to the above-mentioned method is omitted here. The computer device and the computer storage medium are corresponding to the application system performance testing method one to one, and the technical features of the computer device and the storage medium corresponding to the method are not described herein again.
It will be understood by those skilled in the art that all or part of the processes in the methods of the embodiments described above may be implemented by hardware related to instructions of a computer program, and the program may be stored in a non-volatile computer readable storage medium, and in the embodiments of the present invention, the program may be stored in a storage medium of a computer system and executed by at least one processor in the computer system, so as to implement the processes of the embodiments including the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (12)
1. A method for testing application system performance is characterized by comprising the following steps:
acquiring a current first performance parameter;
determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and a fitting function; the fitting function is a curve function of the second performance parameter with respect to the first performance parameter; the first performance parameter and the second performance parameter satisfy a binomial function; the fitting function is obtained by performing curve fitting according to the second performance parameter and the historical data of the first performance parameter;
when the second performance parameter does not belong to a first preset range, updating the first performance parameter according to the first preset range and the fitting function;
when the second performance parameter belongs to a first preset range, acquiring a third performance parameter corresponding to the first performance parameter; before the application system reaches a performance bottleneck, the second performance parameter and the third performance parameter increase as the first performance parameter increases;
if the third performance parameter belongs to a second preset range, recording a test result; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter;
if the third performance parameter does not belong to the second preset range, acquiring a preset updating step length of the second performance parameter;
updating the second performance parameter according to a value obtained by subtracting the preset updating step length from the second performance parameter, and updating the first performance parameter according to the updated second performance parameter and the fitting function;
acquiring a third performance parameter corresponding to the first performance parameter again;
when the third performance parameter belongs to a third preset range, recording a test result;
if the third performance parameter does not belong to the third preset range and the third performance parameter belongs to the second preset range, taking the last-but-one data in the historical data of the second performance parameter as an upper limit and taking the last-but-one data as a lower limit; wherein the third preset range is within the second preset range;
determining a median value according to the upper limit and the lower limit, and updating the first performance parameter according to the median value and the fitting function;
and returning to the step of obtaining the third performance parameter corresponding to the first performance parameter again until the third performance parameter belongs to the third preset range, and recording a test result.
2. The application system performance testing method of claim 1, wherein:
and when the second performance parameter does not belong to a first preset range, updating the first performance parameter according to the fitting function and the maximum value, the minimum value or the average value of the first preset range.
3. The application system performance testing method of claim 1,
and if the third performance parameter does not belong to the third preset range and the third performance parameter does not belong to the second preset range, returning to the step of updating the second performance parameter according to the value obtained by subtracting the preset updating step length from the second performance parameter.
4. The application system performance testing method of claim 3, wherein: the first preset range is not greater than a first threshold and not less than the difference between the first threshold and a first preset fluctuation value; the second preset range is not greater than a second threshold value; the third preset range is not less than the difference obtained by subtracting a second preset fluctuation value from the second threshold value and is not greater than the second threshold value.
5. The method for testing the performance of the application system according to any one of claims 2 to 4, wherein the step of recording the test result is followed by further comprising:
and updating the fitting function according to the test result.
6. An application system performance testing device, comprising:
the current value acquisition module is used for acquiring a current first performance parameter;
the first parameter acquisition module is used for determining a second performance parameter corresponding to the first performance parameter according to the first performance parameter and the fitting function; the fitting function is a curve function of the second performance parameter relative to the first performance parameter, and the first performance parameter and the second performance parameter meet a binomial function; the fitting function is obtained by performing curve fitting according to the second performance parameter and the historical data of the first performance parameter;
the parameter updating module is used for updating the first performance parameter according to the first preset range and the fitting function when the second performance parameter does not belong to the first preset range;
the second parameter acquisition module is used for acquiring a third performance parameter corresponding to the first performance parameter when the second performance parameter belongs to a first preset range; before the application system reaches a performance bottleneck, the second performance parameter and the third performance parameter increase as the first performance parameter increases;
the result recording module is used for recording a test result if the third performance parameter belongs to a second preset range; the test result comprises the first performance parameter, the second performance parameter and the third performance parameter;
the step length obtaining module is used for obtaining a preset updating step length of the second performance parameter if the third performance parameter does not belong to the second preset range;
the index updating module is used for updating the second performance parameter according to a value obtained by subtracting the preset updating step length from the second performance parameter, and updating the first performance parameter according to the updated second performance parameter and the fitting function;
the third parameter acquisition module is used for acquiring a third performance parameter corresponding to the first performance parameter again;
the result recording module comprises:
the test result recording unit is used for recording a test result when the third performance parameter belongs to a third preset range;
an upper and lower limit determining unit, configured to, if the third performance parameter does not belong to the third preset range and the third performance parameter belongs to the second preset range, use last-but-second data in the history data of the second performance parameter as an upper limit and last-but-first data in the history data of the second performance parameter as a lower limit; wherein the third preset range is within the second preset range;
a median determining unit, configured to determine a median according to the upper limit and the lower limit, and update the first performance parameter according to the median and the fitting function;
and the test result recording unit is used for recording a test result when a third performance parameter corresponding to the first performance parameter belongs to the third preset range.
7. The application system performance testing device of claim 6, wherein:
and the parameter updating module is used for updating the first performance parameter according to the fitting function and the maximum value, the minimum value or the average value of the first preset range when the second performance parameter does not belong to the first preset range.
8. The application system performance testing apparatus according to claim 6, further comprising:
and the module calling module is used for calling the index updating module if the third performance parameter does not belong to the third preset range and the third performance parameter does not belong to the second preset range.
9. The application system performance testing device of claim 8, wherein: the first preset range is not greater than a first threshold and not less than the difference between the first threshold and a first preset fluctuation value; the second preset range is not greater than a second threshold value; the third preset range is not less than the difference obtained by subtracting a second preset fluctuation value from the second threshold value and is not greater than the second threshold value.
10. The application system performance testing apparatus according to any one of claims 7 to 9, wherein: further comprising:
and the fitting function updating unit is used for updating the fitting function according to the test result.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the application system performance testing method according to any one of claims 1 to 5 when executing the computer program.
12. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the application system performance testing method of any one of claims 1 to 5.
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