CN113704031B - System pressure testing method, device, medium and equipment - Google Patents
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Abstract
The disclosure relates to a system pressure test method, device, medium and equipment. The method comprises the following steps: acquiring first performance index data of a system under the current concurrency number; determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance index data; determining a next concurrency number for the system pressure test based on the current concurrency number, the first function and the second function; and taking the next concurrency number as the current concurrency number, and triggering and executing to acquire the first performance index data of the system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined. According to the technical scheme, the concurrency number of the system is automatically adjusted through the first performance index data obtained in real time, and the efficiency of system pressure test is improved.
Description
Technical Field
The disclosure relates to the technical field of computer networks, and in particular relates to a system pressure testing method, device, medium and equipment.
Background
Some performance metrics of the business system, such as requests per second and response times, can be used to characterize the amount of pressure that the business system can withstand. The business system is oriented to thousands of users to access, and if the number of users requesting to access the business system at the same time is excessive, the business system can be halted. If the performance of the service system does not reach the standard and is operated online, the loss is likely to be brought to the developer. Therefore, a pressure test is required for the service system before the service system is brought on-line.
The traditional pressure test requires a tester to manually trigger the concurrency number of the system, then the concurrency number is manually adjusted continuously by observing the performance index change condition of the system, and the iteration is always circulated until the optimal solution of the system is found. Therefore, the existing pressure test method not only consumes a great deal of time, but also all pressure test flows need to be regulated and controlled manually, a great deal of manpower is consumed, in addition, the existing pressure test method can be influenced by subjective factors of people, and the optimal solution of the accurate positioning system can not be realized.
Disclosure of Invention
In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a system pressure testing method, device, medium and apparatus.
The present disclosure provides a system pressure testing method, comprising:
acquiring first performance index data of a system under the current concurrency number, wherein the first performance index data comprises a request number per second and response time;
determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance index data;
Determining a next concurrency number for a system pressure test based on the current concurrency number, the first function, and the second function;
and taking the next concurrency number as the current concurrency number, and triggering and executing to acquire first performance index data of the system under the current concurrency number until the maximum per second request number and the corresponding response time of the system are determined.
In some embodiments, prior to obtaining the first performance index data for the system at the current concurrency number, the method further comprises:
acquiring second performance index data of the system under the current concurrency number;
judging whether a preset constraint condition is met or not based on the second performance index data;
acquiring first performance index data of a system under the current concurrency number, wherein the first performance index data comprises:
and when the preset constraint condition is met, acquiring first performance index data of the system under the current concurrency number.
In some embodiments, the second performance index data includes at least one of a central processor occupancy, a memory occupancy, and an interface request error rate;
the preset constraint condition comprises at least one of the following:
the occupancy rate of the central processing unit is smaller than a first occupancy rate threshold value;
The memory occupancy rate is smaller than a second occupancy rate threshold;
the interface request error rate is less than a request error rate threshold.
In some embodiments, the method further comprises:
and when the constraint condition is not met, acquiring first performance index data of the system under the current concurrency number, and taking the request per second in the first performance index data as the maximum request per second of the system.
In some embodiments, determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance metric data comprises:
averaging the request number per second and the response time respectively, and obtaining a first mapping relation between the request number per second and the concurrency number and a second mapping relation between the response time and the concurrency number based on the average value;
and respectively carrying out polynomial fitting on the request per second and the response time by adopting nonlinear regression analysis based on the first mapping relation and the second mapping relation to obtain the first function and the second function.
In some embodiments, determining a next concurrency number for system pressure testing based on the current concurrency number, the first function, and the second function includes:
Determining a first derivative of the first function at the current concurrency number based on the current concurrency number and the first function;
determining a second derivative of the second function at the current concurrency number based on the current concurrency number and the second function;
taking the ratio of the first derivative to the second derivative as a gradient of concurrent number iteration;
and determining the next concurrency number based on the current concurrency number and the gradient.
In some embodiments, determining a maximum number of requests per second for the system includes:
and when the number of requests per second of the system under the current concurrency number is smaller than or equal to the number of requests per second of the system under the last concurrency number, determining that the number of requests per second of the system under the last concurrency number is the maximum number of requests per second.
In some embodiments, prior to determining the first function of the number of requests per second with respect to the number of concurrency and the second function of the response time with respect to the number of concurrency based on the first performance metric data, the method further comprises:
and preprocessing the first performance index data to remove invalid first performance index data.
In some embodiments, preprocessing the first performance index data includes:
Calculating a first standard deviation of the number of requests per second and a second standard deviation of the response time, respectively, based on the first performance index data;
when any one of the first standard deviation and the second standard deviation is smaller than or equal to a preset standard deviation, detecting an abnormal value of the first performance index data;
when the first standard deviation and the second standard deviation are both larger than a preset standard deviation, triggering and executing to acquire first performance index data of the system under the current concurrency number, and detecting an abnormal value of the first performance index data when any one of the first standard deviation and the second standard deviation is smaller than or equal to the preset standard deviation.
In some embodiments, after outlier detection of the first performance index data, the method further comprises:
carrying out averaging treatment on the detected abnormal value;
determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance metric data, comprising:
a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency are determined based on the normal value in the first performance index data and the normalized outlier.
In some embodiments, the method further comprises:
when the number of times of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number reaches a preset number of times, if the first standard deviation and the second standard deviation are both larger than the preset standard deviation, acquiring the first performance index data when the last time of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number, and taking the request number per second in the first performance index data as the maximum request number per second of the system.
The present disclosure provides a system pressure testing device, comprising:
the system comprises a first performance index data acquisition module, a second performance index data acquisition module and a second performance index data processing module, wherein the first performance index data acquisition module is used for acquiring first performance index data of the system under the current concurrency number, and the first performance index data comprises a request number per second and response time;
a concurrency number function determining module for determining a first function of the number of requests per second with respect to the concurrency number and a second function of the response time with respect to the concurrency number based on the first performance index data;
the next concurrency number determining module is used for determining the next concurrency number for the system pressure test based on the current concurrency number, the first function and the second function;
And the repeated execution module is used for taking the next concurrency number as the current concurrency number, triggering and executing to acquire the first performance index data of the system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined.
The present disclosure also provides a computer-readable storage medium storing a program or instructions that cause a computer to perform the steps of any one of the methods described above.
The present disclosure also provides a system pressure testing apparatus, comprising: a processor and a memory;
the processor is configured to perform the steps of any of the methods described above by calling a program or instructions stored in the memory.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
according to the technical scheme provided by the embodiment of the disclosure, based on the current concurrency number of the system and the response time, a first function of the request number per second and the concurrency number of the response time are determined, and a next concurrency number for pressure testing of the system is determined based on the current concurrency number, the first function and the second function, so that the pressure testing is performed on the system under the next concurrency number, and the concurrency number is continuously and automatically adjusted until an optimal solution of the system is obtained, namely, the ultimate performance index value which can be born by the system. Therefore, the technical scheme provided by the embodiment of the disclosure can automatically adjust the concurrency number of the system through the request number per second and the response time acquired in real time under the condition of no human participation, and can quickly find the optimal solution of the system, thereby improving the efficiency of the pressure test of the system and reducing the time and labor cost.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flow chart of a system pressure testing method provided by an embodiment of the present disclosure;
FIG. 2 is a block diagram of a system pressure testing apparatus provided by an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a system pressure testing apparatus according to an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
Currently, the process of performing the pressure test is more often performed with a fixed gradient over a period of time. For example, the initial concurrency number is manually set to 3, then the pressure test is performed on the system with the 3 concurrency number and continuously operated for 30s, a Query Per Second (QPS) Time chart and a Response Time (RT) Time chart within 30s Time can be obtained by using the existing tool (e.g. jmeter tool), then the gradient +3 is further performed on the basis, the Time of 30s is continuously performed with 6 as the concurrency number, the QPS Time chart and the RT Time chart are obtained, and so on until the preset maximum concurrency number is reached, for example, 30s, and finally the maximum QPS and the RT under the corresponding concurrency number of the system are obtained by observing the QPS Time chart and the RT Time chart. However, the pressure test method not only consumes a great deal of time, but also all pressure test flows need to be regulated and controlled manually, a great deal of manpower is consumed, in addition, the existing pressure test method can be influenced by subjective factors of people, and the optimal solution of the accurate positioning system can not be realized.
Aiming at the technical problems, the embodiment of the disclosure provides a system pressure testing method. Specifically, fig. 1 is a flowchart of a system pressure testing method according to an embodiment of the disclosure. The method can be executed by a system pressure testing device, and the device can be realized in a software and/or hardware mode and can be applied to system pressure testing equipment. As shown in fig. 1, the method comprises the steps of:
S110, acquiring first performance index data of the system under the current concurrency number.
Wherein the first performance level data includes requests per second and response times.
In some embodiments, when the system is initially running, the current concurrency number may be manually set by a tester or may be a default value of the system. The embodiment of the disclosure can acquire the request number and the response time per second of the system when the system runs under the current concurrency number in real time by adopting a jmeter tool, wherein the running time of the system under the current concurrency number can be set according to actual conditions, and the method is not limited.
S120, based on the first performance index data, determining a first function of the number of requests per second and the number of concurrency, and a second function of the response time and the number of concurrency.
In an embodiment of the disclosure, the first function and the second function are each continuous nonlinear functions. In practical application, when the system does not reach a saturated state, a first curve corresponding to the first function and a second curve corresponding to the second function are both increased along with the increase of the concurrency number, wherein the slope of the first curve is gradually reduced along with the increase of the concurrency number, and the slope of the second curve is gradually increased along with the increase of the concurrency number. After the system reaches a saturated state, the first curve can be kept unchanged or reduced along with the increase of the concurrency number, while the second curve can be continuously increased along with the increase of the concurrency number, and the increase degree is obviously larger than that when the system does not reach the saturated state.
Since the first performance index data is only obtained at the current concurrency number, in order to obtain a first function of the number of requests per second with respect to the concurrency number and a second function of the response time with respect to the concurrency number, the disclosed embodiments fit the first function and the second function using nonlinear regression analysis. In some embodiments, the request number per second and the response time are averaged respectively, and a first mapping relation between the request number per second and the concurrency number and a second mapping relation between the response time and the concurrency number are obtained based on the average;
based on the first mapping relation and the second mapping relation, nonlinear regression analysis is adopted to perform polynomial fitting on the request number per second and the response time respectively, and a first function and a second function are obtained.
In the disclosed embodiment, the first function is f qps (x)＝a 1 *x 2 +b 1 * x; the second function is f rt (x)＝a 2 *x 3 +b 2 *x 2 +c x; wherein x is a concurrent number, a 1 、b 1 、a 2 、b 2 And c are constants, and are obtained by polynomial fitting by nonlinear regression analysis.
S130, determining the next concurrency number for the system pressure test based on the current concurrency number, the first function and the second function.
Based on the change rule of the curves corresponding to the first function and the second function mentioned in S120, a gradient descent algorithm may be used to find the inflection point of the system. The first function and the second function have different change trends corresponding to curves, are different in slope of the curves in geometric figures, and are different in derivatives of the functions in mathematical formulas. In some embodiments, a first derivative of the first function at the current concurrency number is determined based on the current concurrency number and the first function; determining a second derivative of the second function at the current concurrency number based on the current concurrency number and the second function; taking the ratio of the first derivative to the second derivative as a gradient of concurrent number iteration; based on the current concurrency number and the gradient, a next concurrency number is determined.
Specifically, the following formula is adopted to calculate the next concurrency number:
wherein x is i+1 For the next concurrent number, x i Alpha is learning rate, f 'for current concurrency number' q ′ ps (x i ) At x as a first function i The derivative at (f ', the first derivative' r ′ t (x i ) At x as a second function i The derivative at (i) is the second derivative described above.
In some embodiments, the learning rate determines the convergence speed of the algorithm to a certain extent, according to the relation that the first performance index data changes along with the concurrency number, firstly, the expected concurrency number can change faster earlier, when the system approaches to the saturated state, the change of the request number per second is less obvious along with the change of the concurrency number, and at the moment, the expected concurrency number can change slower, so that the corresponding saturation point can be found more accurately without missing the value of the saturation point because the concurrency number changes too fast, and therefore, the AdaDeltaalgorithm (an optimization algorithm for adaptively adjusting the learning rate) can be adopted to adaptively adjust the value of the learning rate. The specific formula is as follows:
wherein:beta is global learning rate, and the value range is [0.1,1]ρ is an exponential decay rate, typically 0.9 g t Is the gradient of the t-th iteration, E (g 2 ) t Represents the average value of the gradients for the t-round iteration, epsilon represents a minimum, such as 0.000001, to avoid a denominator of 0.
And S140, taking the next concurrency number as the current concurrency number, and triggering and executing to acquire the first performance index data of the system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined.
The step is to iterate the adjusted concurrency number in a loop, namely, the next concurrency number is used as the current concurrency number to execute S110 to S140 until the maximum request number per second and the response time under the corresponding concurrency number of the system are determined, wherein the maximum request number per second and the response time under the corresponding concurrency number are the optimal solution of the system.
In some embodiments, determining a maximum number of requests per second for the system includes:
and when the number of requests per second of the system under the current concurrency number is smaller than or equal to the number of requests per second of the system under the last concurrency number, determining that the number of requests per second of the system under the last concurrency number is the maximum number of requests per second.
According to the system pressure testing method provided by the embodiment of the disclosure, based on the current concurrency number of the system and the response time, a first function of the request number per second and the concurrency number of the response time are determined, and a next concurrency number for the system pressure test is determined based on the current concurrency number, the first function and the second function, so that the system is subjected to pressure test under the next concurrency number, and the concurrency number is automatically adjusted continuously until an optimal solution of the system is obtained, namely, the ultimate performance index value which can be born by the system. Therefore, the technical scheme provided by the embodiment of the disclosure can automatically adjust the concurrency number of the system through the request number per second and the response time acquired in real time under the condition of no human participation, and can quickly find the optimal solution of the system, thereby improving the efficiency of the pressure test of the system and reducing the time and labor cost.
Based on the foregoing technical solution, in some embodiments, before acquiring the first performance index data of the system under the current concurrency number, the method further includes:
a. and acquiring second performance index data of the system under the current concurrency number.
In some embodiments, the second performance index data includes at least one of a central processor occupancy, a memory occupancy, and an interface request error rate.
b. And judging whether a preset constraint condition is met or not based on the second performance index data.
In the embodiment of the disclosure, the preset constraint condition is used to restrict whether to execute the step of the system pressure test method provided in the embodiment of the disclosure, when the second performance index data does not meet the preset constraint condition, it is indicated that the system has reached a saturated state, that is, the number of requests per second of the system reaches a maximum value, so that the step of the system pressure test method is executed only when the second performance index data meets the preset constraint condition. In some embodiments, when the constraint is not satisfied, first performance index data of the system at the current concurrency is obtained, and the number of requests per second in the first performance index data is taken as the maximum number of requests per second of the system.
The preset constraint condition comprises at least one of the following: the occupancy rate of the central processing unit is smaller than a first occupancy rate threshold value; the memory occupancy rate is smaller than a second occupancy rate threshold; the interface request error rate is less than the request error rate threshold. The first occupancy rate threshold, the second occupancy rate threshold and the error rate threshold are set according to actual conditions.
Correspondingly, acquiring first performance index data of the system under the current concurrency number includes: when the preset constraint condition is met, first performance index data of the system under the current concurrency number is obtained.
In some embodiments, prior to determining the first function of the number of requests per second with respect to the number of concurrency and the second function of the response time with respect to the number of concurrency based on the first performance metric data, the method further comprises:
and preprocessing the first performance index data to remove invalid first performance index data. Thus, performance index fluctuation caused by external environment factors such as a network is avoided to the greatest extent.
Because the performance index of the system is affected by external factors such as network state, after the first performance index data is acquired, the first performance index data needs to be preprocessed, and after the first performance index data is judged to be effective, a first function of the number of requests per second about the number of concurrency and a second function of the response time about the number of concurrency are determined based on the first performance index data, otherwise, the obtained result cannot represent the real performance of the system. When the external conditions such as the network are unstable, the request number per second and the response time of the system can generate larger fluctuation, namely the difference between the most of the request number per second in a period of time and the average value of the request number per second in the period of time is larger, and the difference between the most of the response time and the average value of the response time in the period of time is larger. Considering that the standard deviation is a measure of the degree of dispersion of a set of data averages, a larger standard deviation represents a larger difference between most of the values and their averages, and a smaller standard deviation represents values closer to the averages. Therefore, the current stability of the system can be measured by calculating the standard deviation of the request number and the response time per second, and the smaller the standard deviation is, the more stable the system is, and the smaller the influence of external environment factors is.
In some embodiments, preprocessing the first performance index data includes:
calculating a first standard deviation of the number of requests per second and a second standard deviation of the response time based on the first performance index data, respectively; when any one of the first standard deviation and the second standard deviation is smaller than or equal to a preset standard deviation, detecting an abnormal value of the first performance index data; when the first standard deviation and the second standard deviation are both larger than the preset standard deviation, triggering and executing to acquire the first performance index data of the system under the current concurrency number, and detecting an abnormal value of the first performance index data until any one of the first standard deviation and the second standard deviation is smaller than or equal to the preset standard deviation.
In the above embodiment, when the first standard deviation and the second standard deviation are both greater than the preset standard deviation, it is indicated that the fluctuation of the request number per second and the response time is greater, and at this time, the system is unstable, the acquired request number per second and response time cannot reflect the real performance of the system, the request number per second and response time of the system under the current concurrency number need to be reacquired, the second standard deviation of the acquired request number per second and the second standard deviation of the response time need to be reacquired, and the first standard deviation and the second standard deviation of the acquired request number per second and the response time need to be continuously calculated, and compared with the preset standard deviation, the stability of the system is judged, and if the system is unstable, the request number per second and the response time of the system under the current concurrency number need to be reacquired. And the method is circulated until the system is judged to be stable. In addition, when either one of the first standard deviation and the second standard deviation is less than or equal to the preset standard deviation, it is explained that the fluctuation of the request number per second and the response time is large, and the system is unstable at this time, however, there may still be a large difference between the individual request number per second or the response time and the average value, and these large differences from the average value are called outliers. To eliminate the effect of these outliers on subsequent calculations, outliers may be removed or averaged.
The preset standard deviation may include a first preset standard deviation sigma corresponding to the first standard deviation 1 Corresponding to the second standard deviationSecond preset standard deviation sigma 2 . The system running time is T under the current concurrency number, the request number per second and the response time are monitored in real time in the time T, and a data set of the request number per second in the time T, such as D, can be obtained qps ：{d qps1 ,d qps2 ,d qps3 ,……，d qpsn1 Data sets of response times within time T, e.g. D rt ：{d rt1 ,d rt2 ,d rt3 ,……，d rtn2 -a }; then, based on the data set D qps Calculate a first standard deviation sigma of requests per second qps Based on data set D rt Calculating a second standard deviation sigma of the response time rt The method comprises the steps of carrying out a first treatment on the surface of the Respectively comparing the first standard deviation sigma qps With a first preset standard deviation sigma 1 Is of the size of (a) and the second standard deviation sigma rt And a second preset standard deviation sigma 2 When the first standard deviation sigma qps Less than or equal to a first preset standard deviation sigma 1 Or a second standard deviation sigma rt Less than or equal to a second preset standard deviation sigma 2 When the first performance index data is detected, detecting an abnormal value of the first performance index data; when the first standard deviation sigma qps Is greater than a first preset standard deviation sigma 1 And a second standard deviation sigma rt Is greater than a second preset standard deviation sigma 2 And triggering and executing to acquire the first performance index data of the system under the current concurrency number.
In the above embodiment, the abnormal value detection may be performed by a box graph method.
In some embodiments, after outlier detection of the first performance index data, the method further comprises: and carrying out averaging treatment on the detected abnormal value so as to eliminate fluctuation caused by the abnormal value. Accordingly, determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance metric data, comprising: a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency are determined based on the normal value (first performance index data other than the abnormal value) in the first performance index data and the abnormal value after the averaging process. Based on the above embodiment, the normal value and the averaged abnormal value in the first performance index data may be averaged to obtain a mapping relationship between the number of requests per second and the number of concurrences, and a mapping relationship between the response time and the number of concurrences, and then the first function and the second function may be fitted by nonlinear regression analysis based on the mapping relationship.
In some embodiments, the method further comprises:
when the number of times of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number reaches the preset number of times, if the first standard deviation and the second standard deviation are both larger than the preset standard deviation, acquiring the first performance index data when the last time of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number, and taking the request number per second in the first performance index data as the maximum request number per second of the system. Therefore, in order to prevent the operation of triggering the execution acquisition system to perform the first performance index data under the current concurrency number from being infinitely circulated due to the instability of the external factors for a long time, the embodiment sets the upper limit value of the number of times of triggering operation, that is, the preset number of times, so as to end the circulation operation, and meanwhile, when the number of times of triggering the execution acquisition system to perform the first performance index data under the current concurrency number reaches the preset number of times, we consider that the system has reached the maximum request number per second, so that the request number per second acquired last time is taken as the maximum request number per second under the current environment.
Corresponding to the system pressure testing method provided by the embodiment of the disclosure, the embodiment of the disclosure also provides a system pressure testing device. Fig. 2 is a block diagram of a system pressure testing device according to an embodiment of the present disclosure, and as shown in fig. 2, the system pressure testing device includes:
a first performance index data obtaining module 21, configured to obtain first performance index data of the system under the current concurrency number, where the first performance index data includes a request number per second and a response time;
a concurrency function determining module 22 for determining a first function of the number of requests per second with respect to the concurrency and a second function of the response time with respect to the concurrency based on the first performance index data;
a next concurrency number determining module 23, configured to determine a next concurrency number for the system pressure test based on the current concurrency number, the first function, and the second function;
the repeated execution module 24 is configured to take the next concurrency number as the current concurrency number, and trigger to execute and acquire the first performance index data of the system under the current concurrency number until the maximum per second request number and the corresponding response time of the system are determined.
In some embodiments, the system pressure testing apparatus further comprises:
The second performance index data acquisition module is used for acquiring second performance index data of the system under the current concurrency number before acquiring the first performance index data of the system under the current concurrency number;
the constraint condition judging module is used for judging whether a preset constraint condition is met or not based on the second performance index data;
the first performance index data acquisition is used for:
when the preset constraint condition is met, first performance index data of the system under the current concurrency number is obtained.
In some embodiments, the second performance index data includes at least one of a central processor occupancy, a memory occupancy, and an interface request error rate;
the preset constraint condition comprises at least one of the following:
the occupancy rate of the central processing unit is smaller than a first occupancy rate threshold value;
the memory occupancy rate is smaller than a second occupancy rate threshold;
the interface request error rate is less than the request error rate threshold.
In some embodiments, the system pressure testing apparatus further comprises:
and the optimal solution determining module is used for acquiring first performance index data of the system under the current concurrency number when the constraint condition is not met, and taking the request number per second in the first performance index data as the maximum request number per second of the system.
In some embodiments, the concurrency function determination module 22 is to:
averaging the request number and the response time per second respectively, and obtaining a first mapping relation between the request number and the concurrency number per second and a second mapping relation between the response time and the concurrency number based on the average value;
based on the first mapping relation and the second mapping relation, nonlinear regression analysis is adopted to perform polynomial fitting on the request number per second and the response time respectively, and a first function and a second function are obtained.
In some embodiments, the next concurrency determination module 23 is to:
determining a first derivative of the first function at the current concurrency number based on the current concurrency number and the first function;
determining a second derivative of the second function at the current concurrency number based on the current concurrency number and the second function;
taking the ratio of the first derivative to the second derivative as a gradient of concurrent number iteration;
based on the current concurrency number and the gradient, a next concurrency number is determined.
In some embodiments, the optimal solution determination module is further to:
and when the number of requests per second of the system under the current concurrency number is smaller than or equal to the number of requests per second of the system under the last concurrency number, determining that the number of requests per second of the system under the last concurrency number is the maximum number of requests per second.
In some embodiments, the system pressure testing apparatus further comprises:
the data preprocessing module is used for preprocessing the first performance index data before determining a first function of the request number per second about the concurrency number and a second function of the response time about the concurrency number based on the first performance index data so as to reject invalid first performance index data.
In some embodiments, the data preprocessing module is to:
calculating a first standard deviation of the number of requests per second and a second standard deviation of the response time based on the first performance index data, respectively;
when any one of the first standard deviation and the second standard deviation is smaller than or equal to a preset standard deviation, detecting an abnormal value of the first performance index data;
when the first standard deviation and the second standard deviation are both larger than the preset standard deviation, triggering and executing to acquire the first performance index data of the system under the current concurrency number, and detecting an abnormal value of the first performance index data until any one of the first standard deviation and the second standard deviation is smaller than or equal to the preset standard deviation.
In some embodiments, the system pressure testing apparatus further comprises:
the abnormal value processing module is used for carrying out average processing on the detected abnormal value after carrying out abnormal value detection on the first performance index data;
The concurrency function determination module 22 is configured to:
a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency are determined based on the normal value in the first performance index data and the averaged outlier.
In some embodiments, the optimal solution determination module is further to:
when the number of times of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number reaches the preset number of times, if the first standard deviation and the second standard deviation are both larger than the preset standard deviation, acquiring the first performance index data when the last time of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number, and taking the request number per second in the first performance index data as the maximum request number per second of the system.
The system pressure testing device disclosed in the above embodiments can execute the system pressure testing method disclosed in each embodiment, and has the same or corresponding beneficial effects, and in order to avoid repetition, the description is omitted here.
The disclosed embodiments also provide a computer-readable storage medium storing a program or instructions that cause a computer to perform the steps of any of the methods described above.
Illustratively, the program or instructions cause a computer to perform a system stress testing method comprising:
acquiring first performance index data of the system under the current concurrency number, wherein the first performance index data comprises a request number per second and response time;
determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance index data;
determining a next concurrency number for the system pressure test based on the current concurrency number, the first function and the second function;
and taking the next concurrency number as the current concurrency number, and triggering and executing to acquire the first performance index data of the system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined.
Optionally, the computer executable instructions, when executed by the computer processor, may also be used to implement the technical solution of any system pressure testing method provided by the embodiments of the disclosure, so as to achieve the corresponding beneficial effects.
From the above description of embodiments, it will be apparent to those skilled in the art that the disclosed embodiments may be implemented by means of software and necessary general purpose hardware, but may of course also be implemented by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solutions of the embodiments of the present disclosure may be embodied in essence or a portion contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk, or an optical disk of a computer, etc., including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.), to perform the method described in the embodiments of the present disclosure.
On the basis of the foregoing implementation manner, the embodiment of the present disclosure further provides a system pressure testing device, including: a processor and a memory; the processor is used for executing the steps of any one of the methods by calling the program or the instruction stored in the memory, so as to realize the corresponding beneficial effects.
In some embodiments, fig. 3 illustrates a structure of a system pressure testing apparatus provided by an embodiment of the present disclosure. Referring to fig. 3, the system pressure test apparatus may include:
one or more processors 301, one processor 301 being illustrated in fig. 3;
a memory 302;
the system pressure test apparatus may further include: an input device 303 and an output device 304.
The processor 301, memory 302, input device 303 and output device 304 in the system pressure test apparatus may be connected by a bus or other means, the connection of which is illustrated in fig. 3 by way of example by way of a bus connection.
The memory 302 is used as a non-transitory computer readable storage medium, and may be used to store a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the method of an application in an embodiment of the disclosure (e.g., the first performance index data obtaining module 21, the concurrency function determining module 22, the next concurrency determining module 23, and the repeated executing module 24 shown in fig. 2). The processor 301 executes various functional applications of the server and data processing, i.e., implements the methods of the above-described method embodiments, by running software programs, instructions, and modules stored in the memory 302.
Memory 302 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of the electronic device, etc.
In addition, memory 302 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device.
In some embodiments, memory 302 may optionally include memory located remotely from processor 301, which may be connected to the terminal device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 303 may be used to receive entered numeric or character information and to generate key signal inputs related to user settings and function control of the electronic device.
The output device 304 may include a display device such as a display screen.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (12)
1. A system pressure testing method, comprising:
acquiring first performance index data of a system under the current concurrency number, wherein the first performance index data comprises a request number per second and response time;
determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance index data;
determining a next concurrency number for a system pressure test based on the current concurrency number, the first function, and the second function;
taking the next concurrency number as the current concurrency number, triggering and executing to acquire first performance index data of a system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined;
Determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance metric data, comprising:
averaging the request number per second and the response time respectively, and obtaining a first mapping relation between the request number per second and the concurrency number and a second mapping relation between the response time and the concurrency number based on the average value;
based on the first mapping relation and the second mapping relation, respectively performing polynomial fitting on the request per second and the response time by adopting nonlinear regression analysis to obtain a first function and a second function;
determining a next concurrency number for system pressure testing based on the current concurrency number, the first function, and the second function, comprising:
determining a first derivative of the first function at the current concurrency number based on the current concurrency number and the first function;
determining a second derivative of the second function at the current concurrency number based on the current concurrency number and the second function;
taking the ratio of the first derivative to the second derivative as a gradient of concurrent number iteration;
And determining the next concurrency number based on the current concurrency number and the gradient.
2. The method of claim 1, wherein prior to obtaining the first performance index data for the system at the current concurrency, the method further comprises:
acquiring second performance index data of the system under the current concurrency number;
judging whether a preset constraint condition is met or not based on the second performance index data;
acquiring first performance index data of a system under the current concurrency number, wherein the first performance index data comprises:
and when the preset constraint condition is met, acquiring first performance index data of the system under the current concurrency number.
3. The method of claim 2, wherein the second performance index data comprises at least one of a central processing unit occupancy, a memory occupancy, and an interface request error rate;
the preset constraint condition comprises at least one of the following:
the occupancy rate of the central processing unit is smaller than a first occupancy rate threshold value;
the memory occupancy rate is smaller than a second occupancy rate threshold;
the interface request error rate is less than a request error rate threshold.
4. The method according to claim 2, wherein the method further comprises:
And when the constraint condition is not met, acquiring first performance index data of the system under the current concurrency number, and taking the request per second in the first performance index data as the maximum request per second of the system.
5. The method of claim 1, wherein determining a maximum number of requests per second for the system comprises:
and when the number of requests per second of the system under the current concurrency number is smaller than or equal to the number of requests per second of the system under the last concurrency number, determining that the number of requests per second of the system under the last concurrency number is the maximum number of requests per second.
6. The method of claim 1, wherein prior to determining the first function of the number of requests per second with respect to the number of concurrency and the second function of the response time with respect to the number of concurrency based on the first performance metric data, the method further comprises:
and preprocessing the first performance index data to remove invalid first performance index data.
7. The method of claim 6, wherein preprocessing the first performance metric data comprises:
calculating a first standard deviation of the number of requests per second and a second standard deviation of the response time, respectively, based on the first performance index data;
When any one of the first standard deviation and the second standard deviation is smaller than or equal to a preset standard deviation, detecting an abnormal value of the first performance index data;
when the first standard deviation and the second standard deviation are both larger than a preset standard deviation, triggering and executing to acquire first performance index data of the system under the current concurrency number, and detecting an abnormal value of the first performance index data when any one of the first standard deviation and the second standard deviation is smaller than or equal to the preset standard deviation.
8. The method of claim 7, wherein after outlier detection of the first performance level data, the method further comprises:
carrying out averaging treatment on the detected abnormal value;
determining a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency based on the first performance metric data, comprising:
a first function of the number of requests per second with respect to the number of concurrency and a second function of the response time with respect to the number of concurrency are determined based on the normal value in the first performance index data and the normalized outlier.
9. The method of claim 7, wherein the method further comprises:
when the number of times of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number reaches a preset number of times, if the first standard deviation and the second standard deviation are both larger than the preset standard deviation, acquiring the first performance index data when the last time of triggering the execution acquisition system to acquire the first performance index data under the current concurrency number, and taking the request number per second in the first performance index data as the maximum request number per second of the system.
10. A system pressure testing device, comprising:
the system comprises a first performance index data acquisition module, a second performance index data acquisition module and a second performance index data processing module, wherein the first performance index data acquisition module is used for acquiring first performance index data of the system under the current concurrency number, and the first performance index data comprises a request number per second and response time;
a concurrency number function determining module for determining a first function of the number of requests per second with respect to the concurrency number and a second function of the response time with respect to the concurrency number based on the first performance index data;
the next concurrency number determining module is used for determining the next concurrency number for the system pressure test based on the current concurrency number, the first function and the second function;
The repeated execution module is used for taking the next concurrency number as the current concurrency number, triggering and executing to acquire first performance index data of the system under the current concurrency number until the maximum request number per second and the corresponding response time of the system are determined;
the concurrency function determining module is used for:
averaging the request number and the response time per second respectively, and obtaining a first mapping relation between the request number and the concurrency number per second and a second mapping relation between the response time and the concurrency number based on the average value;
based on the first mapping relation and the second mapping relation, respectively carrying out polynomial fitting on the request number per second and the response time by adopting nonlinear regression analysis to obtain a first function and a second function;
the next concurrency number determining module is used for:
determining a first derivative of the first function at the current concurrency number based on the current concurrency number and the first function;
determining a second derivative of the second function at the current concurrency number based on the current concurrency number and the second function;
taking the ratio of the first derivative to the second derivative as a gradient of concurrent number iteration;
based on the current concurrency number and the gradient, a next concurrency number is determined.
11. A computer readable storage medium storing a program or instructions for causing a computer to perform the steps of the method according to any one of claims 1 to 9.
12. A system pressure testing apparatus, comprising: a processor and a memory;
the processor is adapted to perform the steps of the method according to any of claims 1 to 9 by invoking a program or instruction stored in the memory.
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