CN115114029A

CN115114029A - Abnormal file positioning method and device, electronic equipment and storage medium

Info

Publication number: CN115114029A
Application number: CN202210854267.1A
Authority: CN
Inventors: 刘正阳
Original assignee: Beijing Dajia Internet Information Technology Co Ltd
Current assignee: Beijing Dajia Internet Information Technology Co Ltd
Priority date: 2022-07-14
Filing date: 2022-07-14
Publication date: 2022-09-27

Abstract

The disclosure relates to an abnormal file positioning method, an abnormal file positioning device, an electronic device and a storage medium, wherein the method comprises the following steps: under the condition that the utilization rate of computing resources of a server exceeds a utilization rate threshold value, acquiring method stack information of a currently running service on the server in a preset time period from a database; determining a plurality of candidate methods and the number of the use threads corresponding to each candidate method according to the method stack information; the candidate methods represent methods being performed by respective threads within the preset time period, and the number of used threads represents a total number of threads performing any of the candidate methods within the preset time period; and determining a target method causing the utilization rate of the computing resources to exceed the utilization rate threshold value from the plurality of candidate methods based on the number of the using threads, and determining a running file corresponding to the target method as an abnormal file. The method can realize quantitative determination of the target method and improve the accuracy of the determined abnormal file.

Description

Abnormal file positioning method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for locating an abnormal file, an electronic device, a storage medium, and a program product.

Background

The code consumes a CPU (central processing unit) at run time. In ordinary work, finding out which method on the line is served with the most CPU is a very important work for locating the service performance problem, for example, when finding out that the CPU on the line is consumed too much and needs to check which code is caused, it is necessary to find out which method consumes the most CPU.

At present, the technical scheme of the method for positioning the most CPU consumption generally includes that a developer logs in a server to execute some diagnosis commands, and then manually checks which method occupies a wider graph through a graph output by a diagnosis tool, so as to determine which method consumes the most CPU, and further determine an abnormal file.

However, the existing method completely depends on the experience of people, and the positioning result of the method which consumes the most CPU in positioning is often low in accuracy.

Disclosure of Invention

The present disclosure provides an abnormal file positioning method, apparatus, electronic device, storage medium, and program product, to at least solve the problem of low accuracy of positioning results of a method that consumes the most CPU in positioning in related art. The technical scheme of the disclosure is as follows:

according to a first aspect of the embodiments of the present disclosure, there is provided an abnormal file locating method, including:

under the condition that the utilization rate of computing resources of a server exceeds a utilization rate threshold value, acquiring method stack information of a currently running service on the server in a preset time period from a database; the method stack information comprises threads for running the service and methods called by the threads;

determining a plurality of candidate methods and the number of using threads corresponding to the candidate methods according to the method stack information; the candidate methods represent methods being performed by respective threads within the preset time period, and the number of used threads represents a total number of threads performing any of the candidate methods within the preset time period;

and determining a target method causing the utilization rate of the computing resources to exceed the utilization rate threshold value from the plurality of candidate methods based on the number of the using threads, and determining a running file corresponding to the target method as an abnormal file.

In an exemplary embodiment, the determining, according to the method stack information, a plurality of candidate methods and a number of used threads corresponding to each of the plurality of candidate methods includes:

determining a thread stack corresponding to each thread running the service according to the method stack information; the thread stack comprises a method called by the thread from the starting time of running the service to the ending time of the preset time period;

for each thread, determining a candidate method corresponding to the thread from the methods included in the thread stack corresponding to the thread;

and respectively determining the total number of threads executing each candidate method in the preset time period as the number of the used threads corresponding to each candidate method.

In an exemplary embodiment, the determining a candidate method corresponding to the thread from among the methods included in the thread stack corresponding to the thread includes:

acquiring call time corresponding to a method included in the thread stack;

and determining the method with the latest calling time from the methods included in the thread stack as a candidate method corresponding to the thread.

In an exemplary embodiment, the determining a target method from the plurality of candidate methods that results in the computing resource usage exceeding the usage threshold based on the number of usage threads includes:

sequencing the plurality of candidate methods according to the number of the using threads to obtain a candidate method sequence;

determining a target method from the candidate method sequence; the number of using threads corresponding to the target method is greater than the number of using threads corresponding to other candidate methods, which represent methods other than the target method, among the plurality of candidate methods.

In an exemplary embodiment, before obtaining, from a database, method stack information of a service currently running on the server within a preset time period, the method stack information further includes:

acquiring method stack information of a currently running service on the server according to a preset acquisition frequency; the acquisition frequency represents the number of times of acquiring the method stack information in unit time;

and storing the method stack information into a database.

In an exemplary embodiment, before storing the method stack information in a database, the method further includes:

counting the number of the used threads corresponding to the same candidate method in the method stack information collected in the unit time to obtain statistical method stack information;

the storing the method stack information into a database includes:

and storing the statistical method stack information into the database.

In an exemplary embodiment, after determining a target method from the plurality of candidate methods that causes the computing resource usage to exceed a threshold based on the number of threads of use, further comprising:

generating prompt information for the target method;

and sending the prompt information to a user terminal to enable the user terminal to optimize the running file corresponding to the target method.

According to a second aspect of the embodiments of the present disclosure, there is provided an abnormal file locating apparatus, including:

the method comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is configured to acquire method stack information of a service currently running on a server in a preset time period from a database under the condition that the utilization rate of computing resources of the server exceeds a utilization rate threshold value; the method stack information comprises threads for running the service and methods called by the threads;

the determining unit is configured to determine a plurality of candidate methods and the number of using threads corresponding to the candidate methods according to the method stack information; the candidate methods represent methods being performed by respective threads within the preset time period, and the number of used threads represents a total number of threads performing any of the candidate methods within the preset time period;

and the positioning unit is configured to execute a target method which causes the utilization rate of the computing resources to exceed the utilization rate threshold value from the candidate methods based on the number of the using threads, and determine an operation file corresponding to the target method as an abnormal file.

In an exemplary embodiment, the determining unit is further configured to determine, according to the method stack information, a thread stack corresponding to each thread running the service; the thread stack comprises a method called by the thread from the starting time of running the service to the ending time of the preset time period; for each thread, determining a candidate method corresponding to the thread from the methods included in the thread stack corresponding to the thread; and respectively determining the total number of threads executing each candidate method in the preset time period as the number of the used threads corresponding to each candidate method.

In an exemplary embodiment, the determining unit is further configured to execute obtaining of a call time corresponding to a method included in the thread stack; and determining the method with the latest calling time from the methods included in the thread stack as a candidate method corresponding to the thread.

In an exemplary embodiment, the positioning unit is further configured to perform sorting the plurality of candidate methods according to the number of the used threads to obtain a candidate method sequence; determining a target method from the candidate method sequence; the number of using threads corresponding to the target method is greater than the number of using threads corresponding to other candidate methods, which represent methods other than the target method, among the plurality of candidate methods.

In an exemplary embodiment, the apparatus further comprises:

the acquisition unit is configured to execute acquisition of method stack information of a currently running service on the server according to a preset acquisition frequency; the acquisition frequency represents the number of times of acquiring the method stack information in unit time;

a storage unit configured to perform storing the method stack information into a database.

In an exemplary embodiment, the apparatus further includes a statistical unit configured to perform number statistical processing on the used threads corresponding to the same candidate method in the method stack information collected in the unit time to obtain statistical method stack information;

the storage unit is further configured to store the statistical method stack information into the database.

In an exemplary embodiment, the apparatus further comprises a prompt unit configured to perform generating prompt information for the target method; and sending the prompt information to a user terminal to enable the user terminal to optimize the running file corresponding to the target method.

According to a third aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method as described in any one of the above.

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium, in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method of any one of the above.

According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising instructions which, when executed by a processor of an electronic device, enable the electronic device to perform the method as defined in any one of the above.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

under the condition that the utilization rate of computing resources of a server exceeds a utilization rate threshold value, acquiring method stack information of a currently running service on the server in a preset time period from a database; determining a plurality of candidate methods and the number of using threads corresponding to the candidate methods according to the method stack information, determining a target method causing the utilization rate of the computing resources to exceed a utilization rate threshold value from the candidate methods based on the number of using threads, and determining an operation file corresponding to the target method as an abnormal file. The method determines the number of the using threads corresponding to each method executed by the on-line running service through the method stack information, further determines the target method according to the number of the using threads, realizes the quantitative determination of the target method, does not need to depend on manual experience, can improve the accuracy of the determined target method which causes the utilization rate of the computing resources to exceed the utilization rate threshold, and overcomes the defect of low accuracy of a method which manually determines the maximum CPU occupation in the traditional method.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.

FIG. 1 is a diagram illustrating an application environment for an exception file locating method, according to an example embodiment.

Fig. 2 is a flowchart illustrating an abnormal file locating method according to an exemplary embodiment.

Fig. 3 is a flowchart illustrating an abnormal file locating method according to another exemplary embodiment.

FIG. 4 is a flowchart illustrating a method for locating an abnormal file in an application example.

Fig. 5 is a block diagram illustrating an abnormal file locating apparatus according to an exemplary embodiment.

FIG. 6 is a block diagram illustrating an electronic device in accordance with an example embodiment.

Detailed Description

In order to make the technical solutions of the present disclosure better understood, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims. It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) referred to in the present disclosure are both information and data that are authorized by the user or sufficiently authorized by various parties.

In the related art, when positioning an abnormal file, a developer needs to log in a server, a diagnosis command is executed by installing a diagnosis tool to obtain a diagnosis graph, and then the graph occupied by which method is wider is manually checked, so that the most CPU consumed by which method is determined, and the abnormal file is further determined.

The method has two problems, one is that a diagnostic tool needs to be used to locate where the abnormal file is after a problem occurs, and after a developer logs in a server and installs the diagnostic tool to execute a diagnostic command, the problem may be recovered, so that the problem which occurs at the moment cannot be found. Secondly, some data or graphs output by the diagnosis tool need to be seen and judged where the abnormal file is by experience, so that much use cost is increased for problem location.

In order to solve the problems, the disclosure provides an abnormal file positioning method, which is characterized in that performance data of running services are continuously acquired in a server, then the acquired performance data are automatically analyzed, after the utilization rate of a CPU exceeds a certain range, a method which consumes the most CPU at present is automatically analyzed, and the method is sent to a user, so that the defect that the problem cannot be captured due to the fact that the existing scheme relies on user experience to judge and the analysis is carried out only after the service has a problem is solved.

The abnormal file positioning method provided by the embodiment of the disclosure can be applied to the application environment shown in fig. 1. The terminal 102 communicates with a database 104 over a network, the database 104 being used to store performance data (e.g., method stack information) for services running on the server 106. Under the condition that the utilization rate of the computing resources of the server 106 exceeds a utilization rate threshold value, the terminal 102 acquires method stack information of a service running on the server 106 in a preset time period from the database 104, and determines a plurality of candidate methods and the number of using threads corresponding to the candidate methods according to the method stack information; and determining a target method causing the utilization rate of the computing resources to exceed a utilization rate threshold value from a plurality of candidate methods based on the number of the using threads, and determining an operation file corresponding to the target method as an abnormal file. The database 104 may be integrated on the server 106, or may be placed on the cloud or other network server. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 106 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

Fig. 2 is a flowchart illustrating an abnormal file locating method according to an exemplary embodiment, and as shown in fig. 2, the method is described as applied to the terminal 102, and includes the following steps:

in step S210, when the utilization rate of the computing resource of the server exceeds the utilization rate threshold, obtaining, from the database, method stack information of a service currently running on the server within a preset time period; the method stack information includes threads for running services and methods called by the respective threads.

The method stack information represents the execution method information of the service currently running on the server during running.

The thread is the smallest unit that the operating system can perform operation scheduling.

Where a computing resource represents a resource used by a computer while running, for example, the computing resource may be a CPU resource.

The service running on the server may be a service of an application program.

The preset time period may be a time period closest to a time point when the usage of the computing resource of the server exceeds the usage threshold, for example, the last 10 seconds, and the last 5 seconds.

It can be understood that a service running on a server can be regarded as a process, the process may include multiple threads, each thread is a basic unit using a CPU, the nature of the thread running may be understood as the execution of a method (also referred to as a function), information of the method running is stored in a stack frame, information of a return value of the method, a parameter calling another method, and the like are stored in the stack frame, and is denoted as method stack information, and each thread has its own independent and private stack area.

In specific implementation, the method stack information of the currently running service on the server can be continuously acquired through a pre-configured performance data acquisition program and stored in the database. The performance data acquisition program and the currently running service need to be deployed in the same server, so that the performance data acquisition program can acquire running information of the service in real time. The database can provide a storage and query interface, and when the computing resource of the server exceeds the utilization rate threshold, the method stack information of the service running on the server in the latest time period is read through an automatic analysis program installed in the terminal, so that the abnormal file causing the computing resource utilization rate of the server to exceed the utilization rate threshold is determined according to the method stack information in the latest time period.

In practical application, for Java services, the CPU utilization rate of the currently running service can be obtained through Management factory.

In step S220, a plurality of candidate methods and the number of threads to be used corresponding to each of the plurality of candidate methods are determined according to the method stack information.

Wherein the candidate method represents a method that each thread is executing within a preset time period.

Wherein the number of threads used represents the total number of threads executing any of the candidate methods within a preset time period.

In a specific implementation, by using the acquired method stack information, a method that all threads of a service currently running on a server are executing within a preset time period can be determined, the method that each thread is executing within the preset time period is determined as a candidate method, so as to obtain a plurality of candidate methods, and then, for each candidate method, the number of all threads that are executing the candidate method within the preset time period is respectively determined as the number of used threads corresponding to the candidate method.

For example, it is assumed that there are 5 threads scheduled by the currently running service in the server within the preset time period, and the threads are respectively denoted as thread 1, thread 2, …, and thread 5, where the methods being executed by the threads 1 to 5 within the preset time period are respectively: thread 1 → method a, thread 2 → method B, thread 3 → method B, thread 4 → method C, thread 5 → method B. There are 1 threads for executing method a and method C, respectively, and there are 3 threads for executing method B, including thread 2, thread 3, and thread 5, so that the number of threads used for method 1 and method C is 1, and the number of threads used for method B is 3.

In step S230, a target method that causes the computing resource usage to exceed the usage threshold is determined from the plurality of candidate methods based on the number of the usage threads, and a running file corresponding to the target method is determined as an abnormal file.

The target method may represent the first 1 or the first M methods with the largest number of used threads in the candidate methods, that is, the number of used threads corresponding to the target method is greater than the number of used threads corresponding to other candidate methods in the candidate methods, and the other candidate methods represent methods other than the target method in the candidate methods.

The exception file can be understood as a file corresponding to the exception code.

In a specific implementation, the candidate method represents a method that each thread is executing within a preset time period, and the executing method is where the current CPU is consuming, and the number of used threads corresponding to each candidate method may reflect a proportion of CPU consumption of each candidate method. Therefore, the candidate method with the number of threads ranked in the first few bits can be determined from the candidate methods based on the number of threads used corresponding to the candidate methods, the candidate method is used as the target method causing the utilization rate of the computing resources to exceed the utilization rate threshold value, and the code file corresponding to the target method is further used as the abnormal file.

In the abnormal file positioning method, under the condition that the utilization rate of computing resources of the server exceeds a utilization rate threshold value, method stack information of a currently running service on the server in a preset time period is obtained from a database; determining a plurality of candidate methods and the number of using threads corresponding to the candidate methods according to the method stack information, determining a target method causing the utilization rate of the computing resources to exceed a utilization rate threshold value from the candidate methods based on the number of using threads, and determining an operation file corresponding to the target method as an abnormal file. The method determines the number of the using threads corresponding to each method executed by the on-line running service through the method stack information, further determines the target method according to the number of the using threads, realizes the quantitative determination of the target method, does not need to depend on manual experience, can improve the accuracy of the determined target method which causes the utilization rate of the computing resources to exceed the utilization rate threshold, and overcomes the defect of low accuracy of the method which manually determines to occupy the most CPU in the traditional method.

In an exemplary embodiment, in step S220, the multiple candidate methods and the number of threads used by the multiple candidate methods respectively corresponding to the multiple candidate methods are determined according to the method stack information, which may specifically be implemented by the following steps:

step S221, determining a thread stack corresponding to each thread running the service according to the method stack information; the method comprises the steps that a thread stack comprises a method called by the thread from the starting time of running service to the ending time of a preset time period;

step S222, aiming at each thread, determining a candidate method corresponding to the thread from the methods included in the thread stack corresponding to the thread;

step S223, determining the total number of threads executing each candidate method in a preset time period, as the number of used threads corresponding to each candidate method.

Each thread has a corresponding thread stack, and all methods called by the thread from the start time of service operation to the end time of a preset time period (i.e. the time when the utilization rate of the computing resources of the server exceeds the utilization rate threshold) are recorded in the thread stack. For example, the thread stack corresponding to thread 1 is: method A → method B → method C.

In the concrete implementation, after the method stack information of the service currently operated by the server is acquired, each thread has an independent and private stack area, so that the thread stack corresponding to each thread can be determined. Then, for each candidate method, the number of all threads executing the candidate method in a preset time period is counted as the number of used threads corresponding to the candidate method, for example, method C: 3, method E: 1, method F: the format 2 indicates that there are 3 threads currently executing the C method, 1 thread currently executing the E method, and two threads currently executing the F method.

Further, in an exemplary embodiment, in the step S222, the candidate method corresponding to the thread is determined from the methods included in the thread stack corresponding to the thread, and the determining may specifically be implemented by the following steps:

step S222A, obtaining the calling time corresponding to the method included in the thread stack;

step S222B, determining the method with the latest calling time from the methods included in the thread stack as the candidate method corresponding to the thread.

In a specific implementation, since the method included in the thread stack is a method that has been called by the thread, that is, a method that is not called will not appear in the thread stack of the thread, the method whose calling time is closest to the preset time period is a method that is being executed by the thread within the preset time period. Therefore, when determining the candidate method corresponding to each thread, the call time corresponding to the method included in the thread stack corresponding to each thread may be obtained first, and the method with the latest call time in each thread stack may be determined as the candidate method corresponding to each thread.

For example, the acquired method stack information is:

method a → method B → method C;

method D → method E.

The service currently running is represented by two threads, the thread stack of the first thread is method A → method B → method C, the method A executed by the thread is represented, the method A calls the method B, the method B calls the method C, and the method C is the method which is running by the thread. The thread stack for the second thread is method D → method E, representing the D method that the thread executes first, with the D method calling the E method, which is the method that the thread is executing. Thus, the candidate method for the first thread is method C, and the candidate method for the second thread is method E.

In the embodiment, the thread stacks corresponding to the threads are determined through the method stack information, then the method with the latest calling time is determined as the candidate method corresponding to the threads according to the calling time of each method in the thread stacks, and then the number of the used threads corresponding to each candidate method is determined, so that the quantitative evaluation of the occupation condition of each candidate method on the CPU is realized, and the accuracy of the target method determined according to the number of the used threads can be ensured.

In an exemplary embodiment, in the step S230, the method for determining the target method that causes the usage rate of the computing resource to exceed the usage rate threshold from the plurality of candidate methods based on the number of the using threads may specifically be implemented by the following steps:

s231, sequencing a plurality of candidate methods according to the number of the used threads to obtain a candidate method sequence;

step S232, determining a target method from the candidate method sequence; the number of the using threads corresponding to the target method is larger than the number of the using threads corresponding to other candidate methods, and the other candidate methods represent methods except the target method in the plurality of candidate methods.

In the specific implementation, after obtaining the number of the used threads corresponding to each candidate method, the candidate methods can be ranked according to the order of the number of the used threads from large to small to obtain a candidate method sequence, a candidate method with the number of the used threads at the top M (M is a positive integer, and M is more than or equal to 1) is determined from the candidate method sequence and is used as a target method, the number of the used threads corresponding to the target method is larger than the number of the used threads corresponding to other candidate methods, and the target method is guaranteed to be the method which most possibly causes the utilization rate of the computing resources of the server to exceed the utilization rate threshold.

For example, the candidate methods include method C, method E, method F, and method G, and the number of threads used corresponding to each method is method C: 100, method E: 20, method F: 25, method G: 50, sorting the methods according to the number of the used threads from large to small to obtain a candidate method sequence as follows: method C → method G → method F → method E. If the two methods with the largest number of threads are determined from the candidate method sequence, method C and method G can be taken out, and the method C and method G consume the largest amount of CPU in the latest period of time as target methods.

In this embodiment, a plurality of candidate methods are sorted according to the number of used threads, and a candidate method with the number of used threads being N bits first is determined from the obtained candidate method sequence, and is used as a target method, so that the number of used threads corresponding to the target method is greater than the number of used threads corresponding to other candidate methods, and the target method is guaranteed to be a method which most possibly causes the utilization rate of the computing resources of the server to exceed the utilization rate threshold.

In an exemplary embodiment, before the step S210, acquiring, from the database, method stack information of a service running on the server within a preset time period, the method stack information further includes: acquiring method stack information of a currently running service on a server according to a preset acquisition frequency; storing the method stack information in a database.

Wherein the collection frequency represents the number of times of collecting the method stack information in unit time.

In specific implementation, the method stack information of the currently running service on the server can be collected according to a preset collection frequency through a pre-configured performance data collection program and stored in a database, and the performance data collection program and the running service are deployed in the same server, so that the performance data collection program can collect the running information of the service in real time.

For example, the performance data collector may perform the collection action N times per second (N may be configured to be, for example, 100), collecting method stack information of a currently running service on the server, for example, for a Java service, a jstack command (a command for printing stack information of a running Java process) may be used to collect method stack information of the currently running service.

In this embodiment, the method stack information of the service running on the server is continuously acquired by the performance data acquisition program, so that under the condition of an excessively high CPU utilization rate, the method which consumes the most CPU at present can be automatically analyzed, and an abnormal file does not need to be located after a problem occurs, so that the situation that the problem is recovered, which causes a problem which occurs at that time cannot be found can be avoided, and the problem can be conveniently traced.

Further, in an exemplary embodiment, before storing the method stack information in the database, the method further includes: counting the number of the used threads corresponding to the same candidate method in the method stack information collected in unit time to obtain statistical method stack information; and storing the stack information of the statistical method into a database.

In the specific implementation, because the collected method stack information includes a plurality of threads, each thread corresponds to an independent thread stack, in order to quickly determine a target method when the utilization rate of computing resources of a server exceeds a utilization rate threshold, the number of used threads of the same candidate method in the collected method stack information in unit time can be counted to obtain statistical method stack information, and the statistical method stack information is stored in a database.

For example, if the collection frequency of the method stack information of the currently running service on the server is set as 100 times per second, performing number statistics on the used threads corresponding to the same candidate method in the 100 times per second collected method stack information, for example, obtaining a statistical method C: 100, method E: 20, method F: and 25, storing the obtained statistical result and the collected 100 times method stack information into a database together as statistical method stack information.

It is understood that, in practical applications, the number statistical processing may also be performed according to other preset time intervals, for example, the number statistical processing is performed every two seconds, which may be determined according to practical requirements, and the disclosure does not specifically limit this.

In the embodiment, the number of the used threads corresponding to the same candidate method in the collected method stack information in unit time is counted, and the counted statistical method stack information is stored in the database, so that when the utilization rate of the computing resources of the server exceeds the utilization rate threshold, the target method can be directly determined based on the counted number of the used threads, and the efficiency of determining the target method is improved.

In an exemplary embodiment, after determining a target method that causes the computing resource usage to exceed the threshold value from the plurality of candidate methods based on the number of threads used in step S230, the method further includes:

step S240, generating prompt information aiming at the target method;

and step S250, sending prompt information to the user terminal, so that the user terminal optimizes the running file corresponding to the target method.

In the specific implementation, in order to enable a user to timely find a problem causing the utilization rate of the computing resources to exceed the threshold, after a target method causing the utilization rate of the computing resources to exceed the threshold is determined, prompt information for the target method can be generated and sent to the user terminal, so that the user terminal optimizes an operation file corresponding to the target method.

For example, if the target method that causes the usage rate of the computing resource to exceed the threshold is determined to be method C and method G from among the candidate methods, method E, method F and method G, it is described that the most CPU is consumed by method C and method G in the latest period of time, then method C and method G may be stored in the current analysis data, and a prompt message is sent to the user to inform the user that the usage rate of the CPU currently serving is too high and that the most CPU is consumed by several methods are method C and method G.

In this embodiment, after the target method causing the utilization rate of the computing resources to exceed the threshold value is determined, the prompt information for the target method is generated and sent to the user terminal, so that the user can find that the utilization rate of the CPU of the server is too high in time, and can determine the target method causing the too high utilization rate of the CPU, thereby optimizing the running file corresponding to the target method in time.

In another exemplary embodiment, as shown in fig. 3, there is a flowchart illustrating another abnormal file locating method according to an exemplary embodiment, in this embodiment, the method includes the following steps:

step S310, acquiring method stack information of a service currently running on a server according to a preset acquisition frequency, and storing the method stack information into a database;

step S320, under the condition that the utilization rate of the computing resources of the server exceeds a utilization rate threshold value, acquiring method stack information of the currently running service of the server in a preset time period from a database;

step S330, determining a thread stack corresponding to each thread of the running service according to the method stack information; the thread stack comprises a method called by the thread from the starting time of running service to the ending time of a preset time period;

step S340, aiming at each thread, determining a method with the latest calling time from the methods included in the thread stack corresponding to the thread as a candidate method corresponding to the thread;

step S350, respectively determining the total number of threads for executing each candidate method in a preset time period as the number of using threads corresponding to each candidate method;

step S360, determining a target method from a plurality of candidate methods based on the number of the using threads, and determining an operation file corresponding to the target method as an abnormal file; the number of the using threads corresponding to the target method is larger than the number of the using threads corresponding to other candidate methods, and the other candidate methods represent methods except the target method in the multiple candidate methods;

step S370, generating a prompt message for the target method, and sending the prompt message to the user terminal, so that the user terminal optimizes the running file corresponding to the target method.

In the embodiment, the number of the used threads corresponding to each method executed by the on-line running service is determined through the method stack information, and then the target method is determined according to the number of the used threads, so that the quantitative determination of the target method is realized, manual experience is not required, the accuracy of the determined target method which leads the utilization rate of the computing resources to exceed the utilization rate threshold value can be improved, and the defect of low accuracy of a method which manually determines the maximum CPU occupation in the traditional method is overcome.

In an exemplary embodiment, to facilitate an understanding of the disclosed embodiments by those of ordinary skill in the art, reference will now be made to the specific examples illustrated in the drawings. Referring to fig. 4, which is a schematic view of a complete flow of an abnormal file locating method in an application example, as shown in fig. 4, an implementation of the abnormal file locating method of the present disclosure is applied to 5 modules: a performance data acquisition program, a performance data storage database, an automatic analysis program, an analysis data storage database, and an automatic analysis web page, wherein:

and the performance data acquisition program is used for continuously acquiring the execution method stack when the online running service runs to obtain method stack information, and storing the method stack information into a performance data storage database after statistical processing is carried out on the method stack information.

The performance data storage database is used for storing method stack information of each time point (time granularity can be configured, for example, one performance data is stored every minute) of a specific online running service, and provides an interface for storing and querying.

And the automatic analysis program is used for analyzing M methods which consume the most CPU in the current online running service, wherein M can be configured to be 1 for example, and after the analysis is finished, the analysis result is stored in the analysis data storage database.

And the analysis data storage database is used for storing the result data of the performance analysis and providing a storage and query interface.

The automatic analysis web page is a web service, and a user can inquire the performance analysis result in the web page.

The performance data acquisition program and the online running service need to be deployed in the same server, and the performance data storage database, the automatic analysis program and the analysis data storage database can be deployed in the same server as the online running service or in a server different from the online running service.

More specifically, the flow for realizing abnormal file location by the above 5 modules is as follows:

(1) and the performance data acquisition program executes acquisition actions 100 times per second, acquires the method stack information of the online running service and stores the method stack information into a performance data storage database. For example, for a Java service, jstack commands may be used to gather method stack information.

(2) Under the condition that the utilization rate of the CPU which acquires the current on-line running service exceeds a utilization rate threshold value, the method stack information in the latest time period is acquired from a performance data storage database through an automatic analysis program, all methods which are executed by all threads of the current on-line running program are acquired, the candidate method corresponding to each thread is determined from the methods, and the number of the used threads corresponding to each candidate method is counted. And determining several methods with the largest numerical value from the candidate methods according to the number of the used threads, storing the target methods into an analysis data storage database as target methods, generating prompt information aiming at the target methods to a user, and informing the user of the target methods with the largest CPU consumption due to overhigh CPU utilization rate of the current on-line running service.

(3) After receiving the message, the user can access the automatic analysis web page through the browser to view detailed analysis results.

According to the abnormal file positioning method, the service performance data is continuously acquired, the performance data is automatically analyzed, the analysis result is directly displayed to the user, and the defect that the problem cannot be captured in the existing scheme through analysis after the problem occurs in the service and the judgment is carried out by depending on the experience of the user is overcome.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

It is understood that the same/similar parts between the embodiments of the method described above in this specification can be referred to each other, and each embodiment focuses on the differences from the other embodiments, and it is sufficient that the relevant points are referred to the descriptions of the other method embodiments.

Based on the same inventive concept, the embodiment of the present disclosure further provides an abnormal file positioning apparatus for implementing the above-mentioned abnormal file positioning method.

Fig. 5 is a block diagram illustrating an abnormal file locating apparatus according to an exemplary embodiment. Referring to fig. 5, the apparatus includes: an acquisition unit 510, a determination unit 520 and a positioning unit 530, wherein,

an obtaining unit 510 configured to obtain, from a database, method stack information of a service currently running on a server within a preset time period in a case where a usage rate of computing resources of the server exceeds a usage rate threshold; the method stack information comprises threads for running services and methods called by the threads;

a determining unit 520 configured to determine a plurality of candidate methods and a number of used threads corresponding to each of the plurality of candidate methods according to the method stack information; the candidate method represents the method which is executed by each thread in a preset time period, and the number of threads is used for representing the total number of threads which execute any one candidate method in the preset time period;

the positioning unit 530 is configured to execute a target method that causes the usage rate of the computing resource to exceed the usage rate threshold value from the plurality of candidate methods based on the number of the usage threads, and determine an operation file corresponding to the target method as an abnormal file.

In an exemplary embodiment, the determining unit 520 is further configured to determine, according to the method stack information, a thread stack corresponding to each thread running the service; the thread stack comprises a method called by the thread from the starting time of running service to the ending time of a preset time period; for each thread, determining a candidate method corresponding to the thread from the methods included in the thread stack corresponding to the thread; and respectively determining the total number of threads executing each candidate method in a preset time period as the number of the used threads corresponding to each candidate method.

In an exemplary embodiment, the determining unit 520 is further configured to execute obtaining a call time corresponding to a method included in the thread stack; and determining the method with the latest calling time from the methods included in the thread stack as a candidate method corresponding to the thread.

In an exemplary embodiment, the positioning unit 530 is further configured to perform sorting the plurality of candidate methods according to the number of the used threads, so as to obtain a candidate method sequence; determining a target method from the candidate method sequence; the number of the using threads corresponding to the target method is larger than the number of the using threads corresponding to other candidate methods, and the other candidate methods represent methods except the target method in the plurality of candidate methods.

In an exemplary embodiment, the apparatus further comprises:

the acquisition unit is configured to execute acquisition of method stack information of a service currently running on the server according to a preset acquisition frequency; the acquisition frequency represents the number of times of acquiring the method stack information in unit time;

In an exemplary embodiment, the apparatus further includes a statistical unit configured to perform number statistical processing on the used threads corresponding to the same candidate method in the method stack information collected in unit time to obtain statistical method stack information;

the storage unit is further configured to store the stack information of the statistical method in the database.

In an exemplary embodiment, the apparatus further comprises a prompt unit configured to perform generating prompt information for the target method; and sending prompt information to the user terminal to enable the user terminal to optimize the running file corresponding to the target method.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

FIG. 6 is a block diagram illustrating an electronic device 600 for implementing an exception file locating method in accordance with an exemplary embodiment. For example, the electronic device 600 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a gaming console, a tablet device, a medical device, a fitness device, a personal digital assistant, and so forth.

Referring to fig. 6, electronic device 600 may include one or more of the following components: processing component 602, memory 604, power component 606, multimedia component 608, audio component 610, interface to input/output (I/O) 612, sensor component 614, and communication component 616.

The processing component 602 generally controls overall operation of the electronic device 600, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 602 can include one or more modules that facilitate interaction between the processing component 602 and other components. For example, the processing component 602 can include a multimedia module to facilitate interaction between the multimedia component 608 and the processing component 602.

The memory 604 is configured to store various types of data to support operations at the electronic device 600. Examples of such data include instructions for any application or method operating on the electronic device 600, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 604 may be implemented by any type or combination of volatile or non-volatile storage devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, optical disk, or graphene memory.

Power supply component 606 provides power to the various components of electronic device 600. The power components 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 600.

The multimedia component 608 includes a screen providing an output interface between the electronic device 600 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 600 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 610 is configured to output and/or input audio signals. For example, the audio component 610 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 600 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 604 or transmitted via the communication component 616. In some embodiments, audio component 610 also includes a speaker for outputting audio signals.

The I/O interface 612 provides an interface between the processing component 602 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor component 614 includes one or more sensors for providing various aspects of status assessment for the electronic device 600. For example, the sensor component 614 may detect an open/closed state of the electronic device 600, the relative positioning of components, such as a display and keypad of the electronic device 600, the sensor component 614 may also detect a change in the position of the electronic device 600 or components of the electronic device 600, the presence or absence of user contact with the electronic device 600, orientation or acceleration/deceleration of the device 600, and a change in the temperature of the electronic device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 616 is configured to facilitate communications between the electronic device 600 and other devices in a wired or wireless manner. The electronic device 600 may access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component 616 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a computer-readable storage medium comprising instructions, such as the memory 604 comprising instructions, executable by the processor 620 of the electronic device 600 to perform the above-described method is also provided. For example, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, a computer program product is also provided that includes instructions executable by the processor 620 of the electronic device 600 to perform the above-described method.

It should be noted that the descriptions of the above-mentioned apparatus, the electronic device, the computer-readable storage medium, the computer program product, and the like according to the method embodiments may also include other embodiments, and specific implementations may refer to the descriptions of the related method embodiments, which are not described in detail herein.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An abnormal file positioning method is characterized by comprising the following steps:

2. The method of claim 1, wherein determining a plurality of candidate methods and a number of threads to be used for each of the plurality of candidate methods according to the method stack information comprises:

3. The method according to claim 2, wherein the determining a candidate method corresponding to the thread from among the methods included in the thread stack corresponding to the thread comprises:

acquiring call time corresponding to a method included in the thread stack;

4. The method of claim 1, wherein determining a target method from the plurality of candidate methods that results in the computing resource usage exceeding the usage threshold based on the number of usage threads comprises:

5. The method of claim 1, further comprising, before obtaining, from a database, method stack information for a service currently running on the server within a preset time period:

and storing the method stack information into a database.

6. The method of claim 5, prior to storing the method stack information in a database, further comprising:

the storing the method stack information into a database includes:

and storing the statistical method stack information into the database.

7. An abnormal file locating device, comprising:

and the positioning unit is configured to execute a target method which causes the utilization rate of the computing resources to exceed the utilization rate threshold value from the plurality of candidate methods based on the number of the using threads, and determine the running file corresponding to the target method as an abnormal file.

8. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the exception file locating method of any one of claims 1 to 6.

9. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the exception file locating method of any one of claims 1 to 6.

10. A computer program product comprising instructions which, when executed by a processor of an electronic device, enable the electronic device to perform the exception file locating method of any one of claims 1 to 6.