CN111045902A - Pressure testing method and device for server - Google Patents
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Abstract
The embodiment of the invention provides a pressure testing method and device for a server. The method comprises the following steps: acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity; and executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value. The embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost.
Description
Technical Field
The embodiment of the invention relates to the technical field of business support, in particular to a pressure testing method and device of a server.
Background
With the development of mobile communication technology, the architecture of a mobile communication system gradually changes from a traditional type to a micro-service type, which has new requirements for system upgrade and operation and maintenance, and also creates greater challenges, and therefore, the work of determining the system stability becomes more important by performing a pressure test in the system operating environment to detect the system performance.
In the actual pressure testing process, the found problems are very different, real and effective production defects exist, the problems of the test script exist, or a part of the problems that the error is reported but attention is not needed exist. In a limited system pressure test time window, how to ensure that test result information is completely and effectively obtained, and meanwhile, problems can be rapidly classified, irrelevant information is eliminated, and problem processing priority is distinguished, which is the difficulty of pressure test.
In order to solve the above problems, in the prior art, usually, an application log during a pressure test is used as a main entry point, a log platform is used to manually search the application logs of all objects to be tested, and then, problem statistics is performed, and then comparison analysis is performed in combination with the application logs with abnormal pressure tests of the past times, so as to determine whether a problem exists in the system. However, in this scheme, the technical requirements on the service and the system are high, the difficulty of problem analysis is high, and omission or false alarm of abnormal problems is easily caused; and moreover, the log is checked and analyzed in a manual mode, so that the timeliness of the problem is poor, the problem repairing time is short, and the online change and rollback cancellation of the system is easy to cause.
In addition, with landing of the DevOps (combination of Development and Operations), the online and the change are more and more frequent, and the quality pressure test execution which effectively guarantees the online and the change is more and more emphasized, and the number of the pressure tests is inevitably increased. Under the trend that the number of pressure tests is gradually increased, how to ensure the quality of the pressure tests, particularly the quality of the analysis of the pressure test problems, is the key for solving the problems. Although the human power can be increased to a certain extent, automation and intellectualization of test analysis are the great trends of technical development.
Disclosure of Invention
The embodiment of the invention provides a pressure test method and a pressure test device for a server, which are used for solving the problems that a pressure test processing mechanism in the prior art has higher technical requirements on services and systems and has poorer timeliness for finding problems.
In one aspect, an embodiment of the present invention provides a method for testing a server under pressure, where the method includes:
acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field;
obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
On the other hand, an embodiment of the present invention provides a pressure testing apparatus for a server, including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an application error log generated by a server to be tested during pressure test and extracting error information in the application error log, and the error information at least comprises an identification number, a keyword and an error field;
the processing module is used for obtaining an abnormal evaluation value of the error information according to the keywords and the error fields; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
the execution module is used for executing preset processing operation according to the numerical relation between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; the alarm threshold is the alarm threshold of the error type corresponding to the keyword
On the other hand, the embodiment of the present invention further provides an electronic device, which includes a memory, a processor, a bus, and a computer program stored on the memory and executable on the processor, where the processor implements the steps in the stress testing method of the server when executing the program.
In still another aspect, an embodiment of the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the stress testing method of the server.
According to the pressure test method and device for the server, provided by the embodiment of the invention, the error information in the application error log is extracted by acquiring the application error log generated by the server to be tested during pressure test; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; determining whether to execute the alarm or not according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, realizing real-time and automatic detection of an application error log, and analyzing error information; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a pressure testing method for a server according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a first example of an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a pressure testing apparatus of a server according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided only to help the full understanding of the embodiments of the present invention. Thus, it will be apparent to those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
It should be appreciated that reference throughout this specification to "an embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrase "in an embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
In various embodiments of the present invention, it should be understood that the sequence numbers of the following processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.
Fig. 1 shows a flow chart of a pressure testing method for a server according to an embodiment of the present invention.
As shown in fig. 1, the method for testing the stress of the server according to the embodiment of the present invention specifically includes the following steps:
When the server to be tested is detected to perform pressure testing, acquiring an application log (ApplicationLog) of the server according to parameters such as log acquisition (acquisition) start time, acquisition frequency, acquisition duration, acquisition end time and the like configured in advance, and filtering to obtain an application error log. The server to be tested is usually preset with a plurality of application programs, an application log is used for creating, saving and analyzing system messages from the server to be tested, and an application error log is an error log when an application program has an error.
And extracting the identification number, the key word and the error field included in the application error log as the error information of the application error log. The identification number has uniqueness and can comprise the name of the server to be tested and the name of the module (or application program) to which the application error log belongs. The keyword may identify a keyword type of the application error log, and the keyword type may be a preset original error (i.e., an old error) or a newly added error in the present compression.
Each group (or each) of the keywords corresponds to an error type, which may be overload or insufficient memory, etc.
The error field is the specific field where the error occurred.
102, obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormality evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise an error amount index, a keyword type and similarity.
First, a keyword type is determined according to the keyword, the keyword type includes an original error and a newly added error, and optionally, a keyword list may be maintained in advance for storing the keyword of the original error. The error field is then split according to the keyword, and the split field may include: and determining an error amount value included in the error field according to the pre-keyword statement or the post-keyword statement, wherein the error amount value is the number of the same error type, and the error type is a specific error type corresponding to the keyword.
And after the error quantity value is obtained, determining an error quantity index according to the numerical relation between the error quantity value and a preset error reference value, wherein the error quantity index is set to clean the error quantity value and eliminate abnormal values.
And determining similarity, wherein the similarity is a preset numerical value or the similarity between the error text in the error field and the characters of the template according to different types of the keywords.
And obtaining the error amount index, the keyword type and the similarity, and then obtaining the abnormal evaluation value of the error information according to the three parameters.
103, executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
Wherein, the preset processing operation is executed and comprises executing alarm or only recording error information, and the alarm is not executed.
And outputting alarm information carrying the identification number and the error field when the abnormal evaluation value reaches an alarm threshold value of the error type corresponding to the keyword. Since each group of keywords corresponds to an error type, each error type corresponds to an alarm threshold value for a specific server, when the abnormal evaluation value reaches the alarm threshold value, the alarm information is output, and the identification number and the error field are carried in the alarm information, so that the subsequent error processing is facilitated.
When the abnormal evaluation value does not reach the alarm threshold value, only the error information is recorded, and no alarm is given.
And recording the application error date generated by the pressure test, and realizing automatic intelligent updating and perfecting of the error log of the abnormal pressure test problem.
Further, when the alarm information is output, the alarm is executed according to preset alarm parameters, wherein the alarm parameters comprise an alarm time period, an alarm frequency, an alarm form and the like.
In the embodiment of the invention, the error information in the application error log is extracted by acquiring the application error log generated by the server to be tested during the pressure test; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; determining whether to execute the alarm or not according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, realizing real-time and automatic detection of an application error log, and analyzing error information; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost. The embodiment of the invention solves the problems that the processing mechanism of the pressure test in the prior art has higher technical requirements on services and systems and has poorer timeliness for finding the problems.
Optionally, in this embodiment of the present invention, step 102 includes:
step one, determining a keyword type of the keyword; if the keyword is an original keyword, the keyword type is an original error; if the keyword is a newly added keyword, the keyword type is a newly added error;
secondly, performing first preset processing on the error field according to the keyword to obtain the error amount index and the similarity;
step three, the keyword type, the error amount index and the similarity are combined into an error index parameter of the error information;
and fourthly, performing second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information.
In the first step, a keyword type is determined, and based on the keyword extracted in the step 101, whether the keyword is an existing keyword before the current pressure measurement is judged, if yes, the keyword type is an original error, and if not, the keyword type is a newly added error. As described in the foregoing embodiments, a keyword list is maintained in advance, and is used for storing the keywords of the original error and also used for storing the newly added keywords in the newly added error.
In the second step, the first preset processing, namely splitting processing, splits the error field according to the keyword to obtain a pre-keyword statement and/or a post-keyword statement, and further processes the pre-keyword statement and/or the post-keyword statement to determine an error amount value included in the error field. The error quantity value is the number of the same error type, namely the error type corresponding to the keyword.
As a specific example, the specific rule of splitting is: splitting the error field into three parts, namely a sentence before the keyword, the keyword and a sentence after the keyword according to the keyword; and circularly matching all the keywords until the keywords are completely split.
In order to eliminate the abnormal numerical value, after the error quantity numerical value is obtained, the error quantity index is determined according to the numerical relationship between the error quantity numerical value and a preset error reference numerical value.
And step two, determining similarity, wherein the similarity is a preset numerical value or the similarity between the error text in the error field and the characters of the template according to different types of the keywords.
And step three, forming error index parameters by the keyword type, the error amount index and the similarity, and performing second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information.
Further, the step of performing second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information includes:
and respectively carrying out weighted summation on each error index parameter according to a preset weight value to obtain a comprehensive weight value of the error information, wherein the comprehensive weight value is an abnormal evaluation value of the error information.
When the abnormal problem abnormal evaluation value is calculated, a weighting algorithm is adopted to calculate the comprehensive weight of the influence of the error information text based on each single index value. Wherein, the calculation formula is:
N＝∑i＝1WiXi；
wherein N is a comprehensive weight value, and Wi represents the weight of each single index; xi represents the value of each individual index.
For example, if the weights of the three individual indicators are 0.3, 0.5, and 0.2, and the corresponding individual indicator values are 0, 70, and 40, respectively, the comprehensive weight of the effect of the abnormal problem is:
0.3*0+0.5*70+0.2*40＝43。
various single evaluation indexes are configured by introducing rules, the single evaluation indexes are calculated based on split error fields, and finally, a weighting algorithm is adopted to calculate the indexes to obtain a comprehensive weight of the abnormal problem, so that the abnormal problem is judged more accurately, and the defect of dependence on manual experience judgment in the prior art is overcome.
Optionally, based on the foregoing embodiment of the present invention, in step 101, the step of extracting the error information in the application error log includes:
according to a preset semantic analysis algorithm, performing semantic analysis on the application error log to obtain a formatted text of the application error log;
extracting an identification number, a key field and an error field in the formatted text;
carrying out fuzzy matching on the key field and a preset character;
if the matching is successful, the matched preset character is a keyword;
and if the matching fails, extracting the newly added characters in the key fields according to a preset key word extraction algorithm, wherein the newly added characters are key words.
Performing semantic analysis by using an error log based on a preset semantic analysis algorithm to obtain a formatted text in a preset format, outputting formatted text information, and extracting an identification number, a key field and an error field in the formatted text; fuzzy matching is carried out on the key field and a preset character, the preset character is an original wrong key word, and if matching is successful, the matched preset character is the key word; otherwise, extracting new keywords according to a preset keyword extraction algorithm. The preset characters are extracted from log information (error information such as business rule failure and the like for partial normal) aiming at the abnormal previous pressure measurement.
Specifically, keyword extraction is a progressive training process, and newly added keywords (newly added characters) are intelligently sorted out through repeated learning training of error information. The TextRank algorithm can be adopted for calculating to obtain new keywords, and meanwhile, the new keywords are updated to the keyword configuration of the configuration center.
The formula of the TextRank algorithm is as follows:
where Vi represents a word or Chinese character, in (Vi) represents a set of words or Chinese characters, Vj is another set of words or Chinese characters, and out (Vj) also represents a set of words or Chinese characters. Wji represents the weight between Vj and Vi, d is a damping coefficient, the value range is 0 to 1, the probability of word or Chinese character combination is represented, generally set to 0.85, WS (Vj) represents the final weighted value of word combination or Chinese character combination, the larger the value is, the more core is represented; WS (Vj-1) represents the weighting value of Vj-1.
Optionally, in this embodiment of the present invention, the step of performing a first preset process on the error field according to the keyword to obtain the error amount indicator and the similarity includes:
splitting the error field, and determining an error amount index in the error field;
and determining the similarity of the error fields according to the keyword types.
The first preset processing includes splitting processing and determining similarity, and specifically, the step of determining an error amount indicator in the error field includes:
determining an error magnitude value in the error field;
determining an error amount indicator in the error field according to the following formula:
wherein, Y is the error index, X is the error numerical value, A is a preset error threshold value, and B is a first preset parameter value.
Firstly, determining an error quantity value included in an error field, wherein the error quantity value is the number of the same error type, and the error type is an error type corresponding to the keyword. After the error quantity value is obtained, determining an error quantity index according to the formula, wherein if the error quantity value is greater than or equal to a preset error quantity threshold value, the error quantity index is a first preset parameter value; if the error quantity value is smaller than the preset error quantity threshold value, the error quantity index is the product of the ratio of the error quantity value to the preset error quantity threshold value and the first preset parameter value.
Alternatively, the first preset parameter value may be 100 or other values.
The error index is set to clean the error value and eliminate abnormal value.
And, the step of determining the similarity of the error field according to the keyword type includes:
when the keyword type is an original error, the similarity is the character similarity between the error field and the template field of the original error;
and when the keyword type is a newly added error, the similarity is a second preset parameter value.
When the keyword type is an original error, the similarity is the character similarity between the error text in the error field and the template field of the original error, and specifically, the character similarity between the error text in the error field and the template field of the original error can be calculated through a preset similarity algorithm. For example, the error text is used as a character string A, the template field is used as a character string B, and LD (A, B) represents the editing distance between the character string A and the character string B;
a-a 1 a2 … … aN, meaning that a is composed of N characters a1 a2 … … aN, len (a) -N;
B-B1B 2 … … bM, meaning that B is composed of M characters, B1B 2 … … bM, len (B) -M;
define LD (i, j) ═ LD (a1 a2 … … ai, b1 b2 … … bj), where 0 ≦ i ≦ N, 0 ≦ j ≦ M;
therefore, the method comprises the following steps: LD (N, M) ═ LD (a, B);
LD(0，0)＝0；
LD(0，j)＝j；
LD(i，0)＝i；
for i is more than or equal to 1 and less than or equal to N, j is more than or equal to 1 and less than or equal to M;
if ai is bj (i.e., both are similar), then LD (i, j) is LD (i-1, j-1);
if ai ≠ bj (i.e., they are not similar), then LD (i, j) } Min { LD (i-1, j-1), LD (i-1, j), LD (i, j-1) } + 1.
And when the keyword type is a newly added error, directly setting the similarity as a second preset parameter value.
As a first example, referring to fig. 2, fig. 2 provides a pressure testing platform applying the above method, where the pressure testing platform includes a log collection module, an analysis module, an alarm module, and a configuration center;
the server to be tested comprises an application 1, an application 2 and an application 3.
(I) configuration center
The configuration center is mainly responsible for unified management and setting of configuration data of the three modules, is a basic data management center of the whole device and comprises acquisition configuration, keyword configuration, a dynamic resource pool, rule configuration and alarm configuration.
Specifically, the acquisition configuration is mainly responsible for configuring an execution strategy of an acquisition unit component of the log acquisition module, including the log acquisition frequency and interval time of each server to be tested, acquisition timeout time, acquisition retry time configuration parameters, and the like. The collected server name configured here should correspond to the server name in the pressure measurement platform.
The keyword configuration is mainly used for matching error information by the analysis module and judging whether the error information is newly added or historical error, and the main content comprises a server name, a module to which the keyword belongs, a keyword list, a state and the like.
A historical error list is maintained in the dynamic resource pool and used for the analysis module to calculate the similarity of keywords of error information. The dynamic resource pool is an error information set after analysis and positioning in the past, is basic data of the analysis and positioning, and mainly contains error information, error amount, creation time, updating time, effective state, server name, belonging module and other information.
The rule configuration is mainly used for configuring a single evaluation index of an abnormal evaluation value of the abnormal problem calculated by the analysis module. Such as keyword type index, character matching degree index, error amount index, trend change index, etc.
The alarm configuration is mainly used by an alarm module and is used for personalized configuration of alarm thresholds, alarm time periods, alarm frequencies, alarm forms, alarm templates, alarm personnel and the like of each application server.
(II) log collection module
The log acquisition module is mainly used for acquiring an application error log generated by a server to be tested during pressure test and comprises a monitoring unit and an acquisition unit.
The monitoring unit user monitors the dynamic state of the server to be tested for executing the pressure measurement, and monitors the name of the server, the pressure measurement starting time, the pressure measurement ending time, the pressure measurement state data and the like related to the pressure measurement. When the monitoring unit is triggered, the acquisition unit is scheduled to acquire corresponding log information from the server to be tested.
The acquisition unit acquires an application error log generated by a server to be tested during pressure testing according to log capture start time, acquisition frequency and interval time, capture end time and the like of the pressure testing server, and extracts error information in the application error log, wherein the error information at least comprises an identification number, keywords and error fields; and finally, storing in a text set form. The text format after collection and aggregation of the application error log is as follows:
the server name 1| belongs to the module 1| error information 1| error amount 1;
…
the server name N belongs to the module N | error information N | error amount N.
(III) analysis Module
The analysis module is a core module of the platform and is mainly used for obtaining an abnormal evaluation value of the error information according to the keywords and the error fields; the method comprises the steps of analyzing and positioning log information of abnormal problems acquired by an acquisition module to obtain a most real and effective problem list, and dynamically updating keyword configuration and dynamic resource pool data of a configuration center, so that more accurate guarantee is provided for the analysis and positioning of the subsequent abnormal problems of the pressure test. The automatic sorting and positioning device mainly comprises a sorting unit assembly and a positioning unit assembly.
The sorting unit is used for determining the keyword type of the keyword; performing first preset processing on the error field according to the keyword to obtain the error amount index and the similarity; and forming the keyword type, the error amount index and the similarity into an error index parameter of the error information.
And the positioning unit is used for carrying out second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information.
(IV) alarm module
And the alarm module is used for outputting alarm information carrying the identification number and the error field when the abnormal evaluation value reaches an alarm threshold value of the error type corresponding to the keyword.
In the above example, automation and intelligence of application error log analysis are realized, and the problem of excessive consumption of time resources and human resources caused by the need of manually logging in each platform to check corresponding error information is solved. By introducing the technologies of keyword configuration, intelligent updating of dynamic resource pool, calculation of abnormal evaluation value and the like, the accuracy and efficiency of problem analysis and positioning are improved.
In the embodiment of the invention, the error information in the application error log is extracted by acquiring the application error log generated by the server to be tested during the pressure test; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; determining whether to execute the alarm or not according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, realizing real-time and automatic detection of an application error log, and analyzing error information; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost. The embodiment of the invention solves the problems that the processing mechanism of the pressure test in the prior art has higher technical requirements on services and systems and has poorer timeliness for finding the problems.
The pressure testing method of the server according to the embodiment of the present invention is described above, and the pressure testing apparatus of the server according to the embodiment of the present invention will be described below with reference to the accompanying drawings.
Referring to fig. 3, an embodiment of the present invention provides a pressure testing apparatus for a server, including:
an obtaining module 301, configured to obtain an application error log generated by a server under test during a pressure test, and extract error information in the application error log, where the error information at least includes an identification number, a keyword, and an error field.
When the server to be tested is detected to perform pressure testing, acquiring an application log (ApplicationLog) of the server according to parameters such as log acquisition (acquisition) start time, acquisition frequency, acquisition duration, acquisition end time and the like configured in advance, and filtering to obtain an application error log. The server to be tested is usually preset with a plurality of application programs, an application log is used for creating, saving and analyzing system messages from the server to be tested, and an application error log is an error log when an application program has an error.
And extracting the identification number, the key word and the error field included in the application error log as the error information of the application error log. The identification number has uniqueness and can comprise the name of the server to be tested and the name of the module (or application program) to which the application error log belongs. The keyword may identify a keyword type of the application error log, and the keyword type may be a preset original error (i.e., an old error) or a newly added error in the present compression.
Each group (or each) of the keywords corresponds to an error type, which may be overload or insufficient memory, etc.
The error field is the specific field where the error occurred.
A processing module 302, configured to obtain an abnormal evaluation value of the error information according to the keyword and the error field; the abnormality evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise an error amount index, a keyword type and similarity.
First, a keyword type is determined according to the keyword, the keyword type includes an original error and a newly added error, and optionally, a keyword list may be maintained in advance for storing the keyword of the original error. The error field is then split according to the keyword, and the split field may include: and determining an error amount value included in the error field according to the pre-keyword statement or the post-keyword statement, wherein the error amount value is the number of the same error types, and the error types are error types corresponding to the keywords.
And after the error quantity value is obtained, determining an error quantity index according to the numerical relation between the error quantity value and a preset error reference value, wherein the error quantity index is set to clean the error quantity value and eliminate abnormal values.
And determining similarity, wherein the similarity is a preset numerical value or the similarity between the error text in the error field and the characters of the template according to different types of the keywords.
And obtaining the error amount index, the keyword type and the similarity, and then obtaining the abnormal evaluation value of the error information according to the three parameters.
An executing module 303, configured to execute a preset processing operation according to a numerical relationship between the abnormal evaluation value and an alarm threshold; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
Wherein, the preset processing operation is executed and comprises executing alarm or only recording error information, and the alarm is not executed.
And outputting alarm information carrying the identification number and the error field when the abnormal evaluation value reaches an alarm threshold value of the error type corresponding to the keyword. Since each group of keywords corresponds to an error type, each error type corresponds to an alarm threshold value for a specific server, when the abnormal evaluation value reaches the alarm threshold value, the alarm information is output, and the identification number and the error field are carried in the alarm information, so that the subsequent error processing is facilitated.
When the abnormal evaluation value does not reach the alarm threshold value, only the error information is recorded, and no alarm is given. And recording the application error date generated by the pressure test, and realizing automatic intelligent updating and perfecting of the error log of the abnormal pressure test problem.
Further, when the alarm information is output, the alarm is executed according to preset alarm parameters, wherein the alarm parameters comprise an alarm time period, an alarm frequency, an alarm form and the like.
Optionally, in this embodiment of the present invention, the processing module 302 includes:
the determining submodule is used for determining the keyword type of the keyword; if the keyword is an original keyword, the keyword type is an original error; if the keyword is a newly added keyword, the keyword type is a newly added error;
the first processing submodule is used for carrying out first preset processing on the error field according to the keyword to obtain the error amount index and the similarity;
the composition submodule is used for composing the keyword type, the error amount index and the similarity into an error index parameter of the error information;
and the second processing submodule is used for carrying out second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information.
Optionally, in this embodiment of the present invention, the obtaining module 301 includes:
the analysis submodule is used for carrying out semantic analysis on the application error log according to a preset semantic analysis algorithm to obtain a formatted text of the application error log;
the extraction submodule is used for extracting the identification number, the key field and the error field in the formatted text;
the matching submodule is used for carrying out fuzzy matching on the key field and a preset character;
if the matching is successful, the matched preset character is a keyword;
and if the matching fails, extracting the newly added characters in the key fields according to a preset key word extraction algorithm, wherein the newly added characters are key words.
Optionally, in this embodiment of the present invention, the first processing sub-module is configured to:
splitting the error field, and determining an error amount index in the error field;
determining the error type of the error field according to the keyword; if the keyword is an original keyword, the error type is an original error; if the keyword is a newly added keyword, the error type is a newly added error;
determining the similarity of the error fields according to the keyword types;
and forming the error quantity index, the error type and the similarity into an error index parameter of the error information.
Optionally, in this embodiment of the present invention, the determining an error amount indicator in the error field includes:
determining an error magnitude value in the error field;
determining an error amount indicator in the error field according to the following formula:
Y＝min{X/A*B，B}；
wherein, Y is the error index, X is the error numerical value, A is a preset error threshold value, and B is a first preset parameter value.
Optionally, in this embodiment of the present invention, the determining the similarity of the error field according to the keyword type includes:
when the keyword type is an original error, the similarity is the character similarity between the error field and the template field of the original error;
and when the keyword type is a newly added error, the similarity is a second preset parameter value.
Optionally, in this embodiment of the present invention, the second processing sub-module is configured to:
and respectively carrying out weighted summation on each error index parameter according to a preset weight value to obtain a comprehensive weight value of the error information, wherein the comprehensive weight value is an abnormal evaluation value of the error information.
In the above embodiment of the present invention, the obtaining module 301 obtains the application error log generated when the server to be tested performs the pressure test, and extracts the error information in the application error log; the processing module 302 obtains an abnormal evaluation value of the error information according to the keyword and the error field; the execution module 303 determines whether to execute an alarm according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, so that the application error log is automatically detected in real time, and the error information is analyzed; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost.
Fig. 4 is a schematic structural diagram of an electronic device according to yet another embodiment of the present invention.
Referring to fig. 4, an embodiment of the present invention provides an electronic device, which includes a memory (memory)41, a processor (processor)42, a bus 43, and a computer program stored in the memory 41 and running on the processor. The memory 41 and the processor 42 complete communication with each other through the bus 43.
The processor 42 is configured to call the program instructions in the memory 41 to implement the method as provided in the above-mentioned embodiment of the present invention when the program is executed.
In another embodiment, the processor, when executing the program, implements the method of:
acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field;
obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
The electronic device provided in the embodiment of the present invention may be configured to execute a program corresponding to the method in the foregoing method embodiment, and details of this implementation are not described again.
According to the electronic equipment provided by the embodiment of the invention, the error information in the application error log is extracted by acquiring the application error log generated by the server to be tested during pressure test; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; determining whether to execute the alarm or not according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, realizing real-time and automatic detection of an application error log, and analyzing error information; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost.
A further embodiment of the invention provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the method as provided in the above-described embodiments of the invention.
In another embodiment, the program when executed by a processor implements a method comprising:
acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field;
obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
In the non-transitory computer-readable storage medium provided in the embodiment of the present invention, when the program is executed by the processor, the method in the above-described method embodiment is implemented, and details of this implementation are not described again.
According to the non-transitory computer readable storage medium provided by the embodiment of the invention, the error information in the application error log is extracted by acquiring the application error log generated by the server to be tested during the pressure test; obtaining an abnormal evaluation value of the error information according to the keyword and the error field; determining whether to execute the alarm or not according to the numerical relationship between the abnormal evaluation value and the alarm threshold value, realizing real-time and automatic detection of an application error log, and analyzing error information; the abnormal evaluation value is obtained through a plurality of indexes, so that the judgment of the abnormal problem is more accurate, and the defect of dependence on manual experience judgment in the prior art is overcome; the embodiment of the invention realizes automatic and intelligent analysis of abnormal problems in pressure measurement, reduces the difficulty of problem analysis, has lower technical requirements on services and systems, and reduces the labor cost.
Yet another embodiment of the present invention discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the above-mentioned method embodiments, for example comprising:
acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field;
obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A pressure testing method of a server is characterized by comprising the following steps:
acquiring an application error log generated by a server to be tested during pressure testing, and extracting error information in the application error log, wherein the error information at least comprises an identification number, a keyword and an error field;
obtaining an abnormal evaluation value of the error information according to the keyword and the error field; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
executing preset processing operation according to the numerical relationship between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
2. The method according to claim 1, wherein the step of obtaining the abnormal evaluation value of the error information according to the keyword and the error field comprises:
determining a keyword type of the keyword; if the keyword is an original keyword, the keyword type is an original error; if the keyword is a newly added keyword, the keyword type is a newly added error;
performing first preset processing on the error field according to the keyword to obtain the error amount index and the similarity;
forming the keyword type, the error amount index and the similarity into an error index parameter of the error information;
and performing second preset processing on each error index parameter to obtain an abnormal evaluation value of the error information.
3. The method of claim 2, wherein the step of extracting the error information in the application error log comprises:
according to a preset semantic analysis algorithm, performing semantic analysis on the application error log to obtain a formatted text of the application error log;
extracting an identification number, a key field and an error field in the formatted text;
carrying out fuzzy matching on the key field and a preset character;
if the matching is successful, the matched preset character is a keyword;
and if the matching fails, extracting the newly added characters in the key fields according to a preset key word extraction algorithm, wherein the newly added characters are key words.
4. The method according to claim 2, wherein the step of performing a first preset process on the error field according to the keyword to obtain the error amount indicator and the similarity includes:
splitting the error field, and determining an error amount index in the error field;
and determining the similarity of the error fields according to the keyword types.
5. The method of claim 4, wherein the step of determining the error measure in the error field comprises:
determining an error magnitude value in the error field;
determining an error amount indicator in the error field according to the following formula:
wherein, Y is the error index, X is the error numerical value, A is a preset error threshold value, and B is a first preset parameter value.
6. The method of claim 4, wherein the step of determining the similarity of the error fields according to the keyword type comprises:
when the keyword type is an original error, the similarity is the character similarity between the error field and the template field of the original error;
and when the keyword type is a newly added error, the similarity is a second preset parameter value.
7. The method according to claim 2, wherein the step of performing a second preset process on each error index parameter to obtain an abnormal evaluation value of the error information comprises:
and respectively carrying out weighted summation on each error index parameter according to a preset weight value to obtain a comprehensive weight value of the error information, wherein the comprehensive weight value is an abnormal evaluation value of the error information.
8. A pressure testing apparatus for a server, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an application error log generated by a server to be tested during pressure test and extracting error information in the application error log, and the error information at least comprises an identification number, a keyword and an error field;
the processing module is used for obtaining an abnormal evaluation value of the error information according to the keywords and the error fields; the abnormal evaluation value is determined according to error index parameters of the error field, and the error index parameters at least comprise error amount indexes, keyword types and similarity;
the execution module is used for executing preset processing operation according to the numerical relation between the abnormal evaluation value and the alarm threshold value; wherein the preset processing operation comprises executing an alarm or not executing an alarm; and the alarm threshold is an alarm threshold of an error type corresponding to the keyword.
9. An electronic device comprising a memory, a processor, a bus and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the stress testing method of the server according to any one of claims 1 to 7 when executing the program.
10. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that: the program when executed by a processor implements the steps in a stress testing method of a server according to any of claims 1 to 7.
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