Method, apparatus, storage medium and electronic device for reporting buried point data

Abstract

The present application discloses a method, device, storage medium, and electronic device for reporting buried point data, relating to the field of Internet technologies. The method includes: when it is monitored that target buried point data triggers reporting, determining the buried point type corresponding to the data collection buried point of the target buried point data; obtaining, from a local database, the historical data reporting information corresponding to the buried point type; performing abnormal identification processing based on the historical data reporting information to obtain a status identification result of the data collection buried point; and when the status identification result is normal, performing a reporting process on the target buried point data. The present application can avoid the situation of abnormal buried point reporting and improve the reliability of buried point data reporting.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to a method, device, storage medium, and electronic device for controlling the reporting of buried point data. Background Art

[0002] Taking the Android system as an example, currently in all walks of life, there is a need to obtain data in the system for performance analysis. Usually, a solution of setting buried points to collect data for reporting is adopted to obtain data available for performance analysis. In the reporting of buried points, some buried points may appear abnormal, resulting in a large amount of data being reported in a short period, increasing the pressure on the server side and also increasing the work pressure of performance analysts. Therefore, currently, there is a problem that the reliability of buried point data reporting is relatively low due to abnormal reporting. Summary of the Invention

[0003] An embodiment of this application provides a solution that can avoid abnormal reporting of buried points and improve the reliability of buried point data reporting.

[0004] The embodiments of this application provide the following technical solutions:

[0005] According to an embodiment of this application, a method for controlling the reporting of buried point data includes: when it is monitored that target buried point data triggers reporting, determining the buried point type corresponding to the data collection buried point of the target buried point data; obtaining the historical data reporting information corresponding to the buried point type from the local database; performing abnormal identification processing based on the historical data reporting information to obtain the status identification result of the data collection buried point; when the status identification result is normal, performing reporting processing on the target buried point data.

[0006] In some embodiments of this application, the performing abnormal identification based on the historical data reporting information to obtain the status identification result of the data collection buried point includes: obtaining historical reporting status information from the historical data reporting information, where the historical reporting status information is generated when the previous historical buried point data triggered reporting before the current moment, and the type of the data collection buried point of the historical buried point data is the buried point type; if the historical reporting status information is abnormal, determining that the status identification result of the data collection buried point is abnormal; if the historical reporting status information is normal, obtaining the reporting moment of the historical buried point data from the historical data reporting information and determining the status identification result of the data collection buried point according to the reporting moment.

[0007] In some embodiments of the present application, determining the status recognition result of the data collection buried point according to the reporting time includes: if the difference between the reporting time and the current time is less than the target threshold, determining that the status recognition result of the data collection buried point is abnormal; if the difference between the reporting time and the current time is greater than the target threshold, determining that the status recognition result of the data collection buried point is normal.

[0008] In some embodiments of the present application, performing anomaly recognition based on the historical data reporting information to obtain the status recognition result of the data collection buried point includes: collecting the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; using a target anomaly analysis model to perform anomaly recognition processing based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information to obtain at least one status information and the confidence level of each status information; determining the status recognition result of the data collection buried point according to the at least one status information and the confidence level of each status information.

[0009] In some embodiments of the present application, the method further includes: collecting the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; using a target threshold analysis model to perform threshold analysis based on the terminal status information, the module status information, and the historical reporting status information to obtain at least one threshold and the confidence level of each threshold; determining the target threshold according to the at least one threshold and the confidence level of each threshold.

[0010] In some embodiments of the present application, the method further includes: when the status recognition result is abnormal, performing a stop reporting process on the target buried point data.

[0011] In some embodiments of the present application, a buffer and a first interface are established in the log saving process. The first interface is used for being called by a first performance module in the user program space. The log saving process includes a target thread. A target kernel thread, a communication thread, and a second interface are established in the kernel space. The target kernel thread performs cross-thread communication with the target thread through the communication thread. The second interface is used for being called by a second performance module in the user program space. The stopping reporting process of the target buried point data includes: when the collected buried point is in the first performance module and the target buried point data is triggered to be reported by the collected buried point, the first interface is called based on the first performance module, and the target buried point data is saved to the buffer; when the collected buried point is in the second performance module and the target buried point data is triggered to be reported by the collected buried point, the second interface is called based on the second performance module, and the target buried point data is saved to the buffer through the cross-thread communication.

[0012] According to an embodiment of the present application, a device for controlling the reporting of buried point data includes: a monitoring module, configured to determine the buried point type corresponding to the data collection buried point of the target buried point data when it is monitored that the target buried point data triggers reporting; an obtaining module, configured to obtain the historical data reporting information corresponding to the buried point type from a local database; an identifying module, configured to perform abnormal identification processing based on the historical data reporting information to obtain a status identification result of the data collection buried point; and a control module, configured to perform a reporting process on the target buried point data when the status identification result is normal.

[0013] According to another embodiment of the present application, a storage medium stores a computer program thereon. When the computer program is executed by a processor of a computer, the computer is caused to execute the method described in the embodiments of the present application.

[0014] According to another embodiment of the present application, an electronic device may include: a memory storing a computer program; a processor reading the computer program stored in the memory to execute the method described in the embodiments of the present application.

[0015] In the embodiments of the present application, when it is monitored that the target buried point data triggers reporting, the buried point type corresponding to the data collection buried point of the target buried point data is determined; the historical data reporting information corresponding to the buried point type is obtained from a local database; abnormal identification processing is performed based on the historical data reporting information to obtain a status identification result of the data collection buried point; and when the status identification result is normal, the reporting process on the target buried point data is performed.

[0016] In this way, when it is detected that the target buried point data triggers reporting, by determining the buried point type of the data collection buried point that collects the data, and performing anomaly identification processing according to the historical data reporting information corresponding to the buried point type, the status identification result of this type of buried point can be accurately obtained. Furthermore, when the status identification result is normal, the buried point data is reported, which can avoid the situation of abnormal buried point reporting and improve the reliability of buried point data reporting. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Figure 1 FIG. shows a schematic diagram of a system to which the embodiments of the present application can be applied.

[0019] Figure 2 FIG. shows a flowchart of a method for controlling the reporting of buried point data according to an embodiment of the present application.

[0020] Figure 3 FIG. shows a block diagram of a device for controlling the reporting of buried point data according to an embodiment of the present application.

[0021] Figure 4 FIG. shows a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0023] In the following description, specific embodiments of the present application will be described with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and the computer execution referred to herein includes operations of a computer processing unit that represents data in a structured form by electronic signals. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise changed in a manner well known to those skilled in the art. The data structure in which the data is maintained is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present application are described in the above text, which does not represent a limitation, and those skilled in the art will understand that the various steps and operations described below can also be implemented in hardware.

[0024] Figure 1 FIG. shows a schematic diagram of a system 100 to which embodiments of the present application can be applied. As Figure 1 shown, the system 100 may include a server 101 and a terminal 102. The terminal 102 can be any computer device, such as a computer, a mobile phone, a smart watch, and household electrical appliances, etc. The server 101 can be a server cluster or cloud service, etc.

[0025] In an embodiment of this example, the terminal 102 can: when it monitors that the target buried point data triggers reporting, determine the buried point type corresponding to the data collection buried point of the target buried point data; obtain the historical data reporting information corresponding to the buried point type from the local database; perform anomaly identification processing based on the historical data reporting information to obtain the status identification result of the data collection buried point; when the status identification result is normal, perform reporting processing on the target buried point data. Among them, the buried point data can be reported to the server 101.

[0026] Figure 2 FIG. schematically shows a flowchart of a buried point data reporting control method according to an embodiment of the present application. The execution subject of this buried point data reporting control method can be any device, such as Figure 1 the first terminal 102 shown.

[0027] As Figure 2 shown, this buried point data reporting control method may include step S210 to step S240.

[0028] Step S210, when it monitors that the target buried point data triggers reporting, determine the buried point type corresponding to the data collection buried point of the target buried point data;

[0029] Step S220, obtain the historical data reporting information corresponding to the buried point type from the local database;

[0030] Step S230: Perform anomaly recognition processing based on the historical data reporting information to obtain the status recognition result of the data collection data points.

[0031] Step S240: When the status recognition result is normal, perform reporting processing on the target data point data.

[0032] Data collection data points refer to the embedding of data collection codes in the device. Target data point data refers to the data in the device collected by the data collection data points. The reporting of the target data point data can be triggered by the data collection data points themselves, or can be caused by the repeated processing of the data point data collected by the data collection data points by the data point data processing logic in the device.

[0033] When it is monitored locally that the reporting of the target data point data is triggered, determine the data point type corresponding to the data collection data point of the target data point data. The data point type is the type of the data collection data point itself. In one implementation, the data point type corresponds to the terminal performance module in the device. The terminal performance module is, for example, the kernel module. At this time, the type of a certain data collection data point can be the kernel type. Among them, multiple (such as at least two) data collection data points can correspond to the kernel type. For example, the kernel module can include sub-modules such as the Mem sub-module, the CPU sub-module, and the I0 sub-module, and each sub-module can correspond to a data collection data point.

[0034] Data summary information (such as collection location information and data point marking information, etc.) can be extracted from the target data point. Then, based on the data summary information, the data collection data point of the target data point data can be determined by querying the information configuration table, and further, the data point type of the data collection data point of the target data point data can be determined from the query information configuration table.

[0035] The local database can collect local data reporting records and manage the data reporting records by type based on the data point type. Based on the determined data point type, the historical data reporting information corresponding to the determined data point type can be obtained from the database. The historical data reporting information is the data reporting historical records of all data points of this data point type.

[0036] The historical data reporting information can reflect the reporting rules of the data collection data points of this type. Furthermore, by performing anomaly recognition processing based on the historical data reporting information, the status recognition result of the data collection data point can be accurately obtained. The status recognition result is the recognition result of whether the data collection data point is in a normal reporting state.

[0037] Furthermore, when the status recognition result is normal, performing reporting processing on the data point data can avoid the situation of abnormal data point reporting.

[0038] In this way, based on steps S210 to S240, when it is detected that the target buried point data triggers reporting, by determining the buried point type of the data collection buried point that collects this data and performing anomaly recognition processing according to the historical data reporting information corresponding to this buried point type, the status recognition result of this type of buried point can be accurately obtained. Furthermore, when the status recognition result is normal, the buried point data is reported, which can avoid the situation of abnormal buried point reporting and improve the reliability of buried point data reporting.

[0039] The following describes the specific processes of the respective steps performed when controlling the reporting of buried point data.

[0040] In step S210, when it is monitored that the target buried point data triggers reporting, determine the buried point type corresponding to the data collection buried point of the target buried point data.

[0041] A data collection buried point is the embedding of the data collection code in the collection device, and the target buried point data is the data in the device collected by the data collection buried point. The reporting of the target buried point data can be triggered by the data collection buried point itself or by the buried point data processing logic in the device repeatedly processing the buried point data collected by the data collection buried point, etc.

[0042] When it is monitored locally that the target buried point data triggers reporting, determine the buried point type corresponding to the data collection buried point of the target buried point data. The buried point type is the type of the data collection buried point itself. In one implementation, the buried point type corresponds to a performance module in the device, such as a kernel module. At this time, the type of a certain data collection buried point can be the kernel type, and multiple (such as at least two) data collection buried points can correspond to the kernel type.

[0043] Data summary information (such as collection location information and buried point marking information, etc.) can be extracted from the target data buried point, and then based on the data summary information, the data collection buried point of the target buried point data can be determined by querying the information configuration table, and further the buried point type of the data collection buried point of the target buried point data can be determined from the query information configuration table.

[0044] In step S220, obtain the historical data reporting information corresponding to the buried point type from the local database;

[0045] The local database can collect local data reporting records and manage the data reporting records by type based on the buried point type. Based on the determined buried point type, the historical data reporting information corresponding to the determined buried point type can be obtained from the database. The historical data reporting information is the data reporting historical records of all buried points of this buried point type.

[0046] Among them, locally, each time data reporting is triggered, information such as the reporting time of the buried point data can be recorded to form a historical data reporting record.

[0047] In step S230, perform anomaly recognition processing based on the historical data reporting information to obtain the status recognition result of the data collection data point;

[0048] The historical data reporting information can reflect the reporting pattern of this type of data collection data point. Furthermore, by performing anomaly recognition processing based on the historical data reporting information, the status recognition result of the data collection data point can be accurately obtained, and this status recognition result is the recognition result of whether the data collection data point is in a normal reporting state.

[0049] In one embodiment, step S230 of performing anomaly recognition based on the historical data reporting information to obtain the status recognition result of the data collection data point includes:

[0050] Obtain historical reporting status information from the historical data reporting information. The historical reporting status information is generated when the previous historical data point data triggered a report before the current moment, and the type of the data collection data point of the historical data point is the data point type; if the historical reporting status information is abnormal, determine that the status recognition result of the data collection data point is abnormal; if the historical reporting status information is normal, obtain the reporting moment of the historical data point from the historical data reporting information, and determine the status recognition result of the data collection data point according to the reporting moment.

[0051] The historical reporting status information is generated when the previous historical data point data triggered a report before the current moment, and the type of the data collection data point of the historical data point is the data point type. Therefore, this historical reporting status information can reflect whether the previous data reporting status of this data point type is normal. To a certain extent, the previous data reporting status can reflect the status at the current moment.

[0052] Furthermore, if the historical reporting status information is abnormal, directly determine that the status recognition result of the data collection data point is abnormal, which can effectively avoid abnormal reporting.

[0053] Further, if the historical reporting status information is normal, obtain the reporting moment of the historical data point from the historical data reporting information, and determine the status recognition result of the data collection data point according to the reporting moment, which can further accurately verify whether the current report is abnormal and ensure the reliability of the reporting management.

[0054] In one embodiment, determining the status recognition result of the data collection data point according to the reporting moment includes: if the difference between the reporting moment and the current moment is less than the target threshold, determine that the status recognition result of the data collection data point is abnormal; if the difference between the reporting moment and the current moment is greater than the target threshold, determine that the status recognition result of the data collection data point is normal.

[0055] If the difference between the reporting time of the historical buried-point data and the current time is less than the target threshold, it indicates that the reporting frequency is too high. At this time, the status recognition result of the data collection buried point is determined to be abnormal, and further abnormal reporting is avoided. On the contrary, reporting is allowed.

[0056] In one embodiment, it further includes a method for determining the target threshold to adaptively and accurately obtain the target threshold and improve the accuracy of abnormal judgment: collecting the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; using the target threshold analysis model to perform threshold analysis based on the terminal status information, the module status information, and the historical reporting status information to obtain at least one threshold and the confidence level of each threshold; and determining the target threshold according to the at least one threshold and the confidence level of each threshold.

[0057] The terminal status information is the global status information of the terminal itself, which may include the number of tasks running on the collected terminal, the task information of the running tasks, and the CPU occupancy status and other information. The terminal performance module corresponding to the data collection buried point is a specific performance module in the terminal. The performance module is, for example, a kernel module, and the data collection buried point is used to collect data for the corresponding terminal performance module. The module status information is the specific status information in the terminal performance module.

[0058] The target threshold analysis model is an intelligent model based on deep learning, and the target threshold analysis model is pre-trained through the collected training samples. Using the target threshold analysis model, threshold analysis is performed based on the terminal status information, the module status information, and the historical reporting status information to obtain at least one threshold and the confidence level of each threshold. Then, an accurate threshold (such as the threshold with the highest confidence level) can be selected as the target threshold according to the confidence level to achieve adaptive update of the target threshold.

[0059] It can be understood that in some embodiments, the target threshold can be an empirical value set according to actual needs, which can ensure the judgment accuracy to a certain extent.

[0060] In one embodiment, the abnormal recognition based on the historical data reporting information to obtain the status recognition result of the data collection buried point includes:

[0061] Collect the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection point of the target buried point data; use the target anomaly analysis model to perform anomaly recognition processing based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information, and obtain at least one status information and the confidence level of each status information; determine the status recognition result of the data collection point according to the at least one status information and the confidence level of each status information.

[0062] The terminal status information is the global status information of the terminal itself, which may include information such as the number of tasks running on the collected terminal, the task information of the running tasks, and the CPU occupancy status. The terminal performance module corresponding to the data collection point is a specific performance module in the terminal. The performance module is, for example, a kernel module, and the data collection point is used to collect data from the corresponding terminal performance module. The module status information is the specific status information in the terminal performance module.

[0063] The target anomaly analysis model is an intelligent model based on deep learning, and the target anomaly analysis model is pre-trained through the collected training samples. Use the target threshold analysis model to perform anomaly recognition processing based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information, and obtain at least one status information and the confidence level of each status information. Then, the accurate status information (such as the status information with the highest confidence level) can be selected according to the confidence level as the status recognition result to further improve the judgment accuracy of the status recognition result.

[0064] In step S240, when the status recognition result is normal, report the target buried point data.

[0065] When the status recognition result is normal, reporting the buried point data can avoid the situation of abnormal buried point reporting and improve the reliability of buried point data reporting.

[0066] In one embodiment, it further includes: when the status recognition result is abnormal, stop reporting the target buried point data.

[0067] For the stop reporting process, in one example, the buried point data can be deleted, and in another example, the target buried point data can be locally cached.

[0068] When locally caching target buried point data, in one embodiment, a buffer area and a first interface are established in the log saving process. The first interface is used to be called by a first performance module in the user program space. The log saving process includes a target thread. A target kernel thread, a communication thread, and a second interface are established in the kernel space. The target kernel thread performs cross-thread communication with the target thread through the communication thread. The second interface is used to be called by a second performance module in the user program space. The process of stopping reporting the target buried point data includes: when the collected buried point is in the first performance module, based on the first performance module calling the first interface, saving the target buried point data to the buffer area; when the collected buried point is in the second performance module, based on the second performance module calling the second interface, saving the target buried point data to the buffer area through the cross-thread communication.

[0069] Both the first performance module and the second performance module are terminal performance modules in the terminal. The first performance module is located in the user program space (i.e., userspace). The first performance module may include modules such as the AMS module, Looper module, Native module, Recents module, Contact module, and Mms module. The second performance module is located in the kernel space (i.e., kernelspace). The second performance module may include modules such as the Mem module, CPU module, and I0 module.

[0070] The log saving process is the logd process. By establishing a buffer area and a first interface in the log saving process, the first interface is used to be called by a first performance module in the user program space, and the log saving process includes a target thread. A target kernel thread, a communication thread, and a second interface are established in the kernel space. The target kernel thread performs cross-thread communication with the target thread through the communication thread. The second interface is used to be called by a second performance module in the user program space. In this way, a unified management framework for performance modules in the user program space and the kernel space can be realized. Based on this framework, the coupling between data collection buried points can be reduced, and data caching is convenient and reliable. When abnormal reporting occurs for data collection buried points in different performance modules, cache processing can be conveniently and reliably implemented, and effective coordination of avoiding reporting and data saving can be achieved.

[0071] Specifically, when stopping the reporting process, when the collection point of the target buried point data is in the first performance module and the target buried point data is triggered for reporting by the collection point, the first interface is called based on the first performance module, and the target buried point data is saved to the buffer; when the collection point is in the second performance module and the target buried point data is triggered for reporting by the collection point, the second interface is called based on the second performance module, and the target buried point data is saved to the buffer through cross-thread communication, which can further facilitate, reliably, and low-couplingly control the exceptions of the buried point data.

[0072] To facilitate better implementation of the buried point data reporting control method provided by the embodiments of the present application, the embodiments of the present application further provide a buried point data reporting control device based on the above buried point data reporting control method. The meanings of the terms are the same as those in the above buried point data reporting control method, and the specific implementation details can refer to the descriptions in the method embodiments. Figure 3 The block diagram of a buried point data reporting control device according to an embodiment of the present application is shown.

[0073] As Figure 3 shown, the buried point data reporting control device 300 may include a monitoring module 310, an obtaining module 320, an identifying module 330, and a control module 340.

[0074] The monitoring module 310 may be used to determine the type of the buried point corresponding to the data collection point of the target buried point data when it is detected that the target buried point data triggers reporting; the obtaining module 320 may be used to obtain the historical data reporting information corresponding to the buried point type from the local database; the identifying module 330 may be used to perform exception identification processing based on the historical data reporting information to obtain the status identification result of the data collection point; the control module 340 may be used to report the target buried point data when the status identification result is normal.

[0075] In some embodiments of the present application, the identifying module 330 includes: a status information obtaining unit, configured to obtain historical reporting status information from the historical data reporting information, where the historical reporting status information is generated when the previous historical buried point data triggers reporting before the current moment, and the type of the data collection point of the historical buried point data is the buried point type; a first identifying unit, configured to determine that the status identification result of the data collection point is abnormal if the historical reporting status information is abnormal; a second identifying unit, configured to obtain the reporting time of the historical buried point data from the historical data reporting information if the historical reporting status information is normal, and determine the status identification result of the data collection point according to the reporting time.

[0076] In some embodiments of the present application, the second recognition unit is configured to: if the difference between the reporting time and the current time is less than the target threshold, determine that the status recognition result of the data collection data point is abnormal; if the difference between the reporting time and the current time is greater than the target threshold, determine that the status recognition result of the data collection data point is normal.

[0077] In some embodiments of the present application, the recognition module 330 includes: an information collection unit, configured to collect the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection data point of the target data point; a model analysis unit, configured to perform anomaly recognition processing based on the terminal status information, the module status information, and the historical reporting status information by using a target anomaly analysis model to obtain at least one status information and the confidence level of each status information; a result determination unit, configured to determine the status recognition result of the data collection data point according to the at least one status information and the confidence level of each status information.

[0078] In some embodiments of the present application, the device further includes a threshold update unit, configured to: collect the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection data point of the target data point; perform threshold analysis based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information by using a target threshold analysis model to obtain at least one threshold and the confidence level of each threshold; determine the target threshold according to the at least one threshold and the confidence level of each threshold.

[0079] In some embodiments of the present application, the device further includes a stop control model, configured to: when the status recognition result is abnormal, perform a stop reporting process on the target data point data.

[0080] In some embodiments of the present application, a buffer and a first interface are established in the log saving process. The first interface is used for being called by a first performance module in the user program space. The log saving process includes a target thread. A target kernel thread, a communication thread, and a second interface are established in the kernel space. The target kernel thread performs cross-thread communication with the target thread through the communication thread. The second interface is used for being called by a second performance module in the user program space. The stop control model includes: a first control unit, configured to, when the collection hook point is located in the first performance module and the target hook point data is triggered to be reported by the collection hook point, call the first interface based on the first performance module, and save the target hook point data to the buffer; a second control unit, configured to, when the collection hook point is located in the second performance module and the target hook point data is triggered to be reported by the collection hook point, call the second interface based on the second performance module, and save the target hook point data to the buffer through the cross-thread communication.

[0081] In this way, based on the hook point data reporting control device 300, when it is detected that the target hook point data triggers reporting, by determining the hook point type of the data collection hook point that collects the data, and performing abnormal identification processing according to the historical data reporting information corresponding to the hook point type, the status identification result of this type of hook point can be accurately obtained. Furthermore, when the status identification result is normal, the hook point data is reported, which can avoid the situation of abnormal hook point reporting and improve the reliability of hook point data reporting.

[0082] It should be noted that although several modules or units of a device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0083] In addition, an embodiment of the present application further provides an electronic device, which can be a terminal or a server. As Figure 4 shown, it shows a schematic structural diagram of the electronic device involved in the embodiment of the present application. Specifically:

[0084] The electronic device may include a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, an input unit 404 and other components. Those skilled in the art can understand that Figure 4 the structural diagram of the electronic device shown in does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Among them:

[0085] The processor 401 is the control center of the electronic device, connecting various parts of the entire computer device through various interfaces and circuits. By running or executing software programs and / or modules stored in the memory 402, and by calling the data stored in the memory 402, it executes various functions of the computer device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interfaces, and application programs, etc., and the modem processor mainly processes wireless communications. It can be understood that the above-mentioned modem processor may not be integrated into the processor 401 either.

[0086] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the computer device. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. Correspondingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0087] The electronic device further includes a power supply 403 for supplying power to each component. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, so as to realize functions such as management of charging, discharging, and power consumption management through the power management system. The power supply 403 may also include any components such as one or more DC or AC power supplies, a recharge system, a power failure detection circuit, a power converter or inverter, and a power status indicator.

[0088] The electronic device may further include an input unit 404, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.

[0089] Although not shown, the electronic device may further include a display unit and the like, which will not be elaborated here. Specifically, in this embodiment, the processor 401 in the electronic device will load the executable files corresponding to the processes of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 will run the computer programs stored in the memory 402 to implement various functions. For example, the processor 401 may execute the following steps:

[0090] When it is monitored that the target buried point data triggers a report, determine the buried point type corresponding to the data collection buried point of the target buried point data; obtain the historical data report information corresponding to the buried point type from the local database; perform anomaly recognition processing based on the historical data report information to obtain the status recognition result of the data collection buried point; when the status recognition result is normal, perform a report process on the target buried point data.

[0091] In some embodiments of the present application, the performing anomaly recognition based on the historical data report information to obtain the status recognition result of the data collection buried point includes: obtaining historical report status information from the historical data report information, where the historical report status information is generated when the previous historical buried point data triggered a report before the current moment, and the type of the data collection buried point of the historical buried point data is the buried point type; if the historical report status information is abnormal, determine that the status recognition result of the data collection buried point is abnormal; if the historical report status information is normal, obtain the report moment of the historical buried point data from the historical data report information, and determine the status recognition result of the data collection buried point according to the report moment.

[0092] In some embodiments of the present application, the determining the status recognition result of the data collection buried point according to the report moment includes: if the difference between the report moment and the current moment is less than the target threshold, determine that the status recognition result of the data collection buried point is abnormal; if the difference between the report moment and the current moment is greater than the target threshold, determine that the status recognition result of the data collection buried point is normal.

[0093] In some embodiments of the present application, the abnormal recognition based on the historical data reporting information to obtain the status recognition result of the data collection buried point includes: collecting the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; using a target abnormal analysis model to perform abnormal recognition processing based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information to obtain at least one status information and the confidence level of each status information; and determining the status recognition result of the data collection buried point according to the at least one status information and the confidence level of each status information.

[0094] In some embodiments of the present application, the method further includes: collecting the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; using a target threshold analysis model to perform threshold analysis based on the terminal status information, the module status information, and the historical reporting status information to obtain at least one threshold and the confidence level of each threshold; and determining the target threshold according to the at least one threshold and the confidence level of each threshold.

[0095] In some embodiments of the present application, the method further includes: when the status recognition result is abnormal, performing a stop reporting process on the target buried point data.

[0096] In some embodiments of the present application, a buffer and a first interface are established in the log saving process, the first interface is used for being called by a first performance module in the user program space, and the log saving process includes a target thread; a target kernel thread, a communication thread, and a second interface are established in the kernel space, the target kernel thread performs cross-thread communication with the target thread through the communication thread, and the second interface is used for being called by a second performance module in the user program space; the performing a stop reporting process on the target buried point data includes: when the collection buried point is in the first performance module and the target buried point data is triggered to be reported by the collection buried point, calling the first interface based on the first performance module to save the target buried point data to the buffer; and when the collection buried point is in the second performance module and the target buried point data is triggered to be reported by the collection buried point, calling the second interface based on the second performance module to save the target buried point data to the buffer through the cross-thread communication.

[0097] Those of ordinary skill in the art can understand that all or part of the steps in the above various methods can be completed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0098] To this end, the embodiments of the present application further provide a storage medium, in which a computer program is stored, and the computer program can be loaded by a processor to execute the steps in any of the methods provided by the embodiments of the present application.

[0099] Among them, the storage medium may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.

[0100] Since the computer program stored in the storage medium can execute the steps in any of the methods provided by the embodiments of the present application, the beneficial effects achievable by the methods provided by the embodiments of the present application can be realized. For details, see the previous embodiments and will not be elaborated here.

[0101] After considering the specification and practicing the disclosed embodiments herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common general knowledge or conventional technical means in the technical field not disclosed in the present application.

[0102] It should be understood that the present application is not limited to the embodiments already described and shown in the drawings, but various modifications and changes can be made without departing from its scope.

Claims

1. A method for controlling the reporting of buried point data, characterized in that Including: When it is detected that the target buried point data triggers reporting, determine the buried point type corresponding to the data collection buried point of the target buried point data; Obtain the historical data reporting information corresponding to the buried point type from the local database; Perform anomaly recognition processing based on the historical data reporting information to obtain the status recognition result of the data collection buried point; When the status recognition result is normal, perform reporting processing on the target buried point data; The performing anomaly recognition based on the historical data reporting information to obtain the status recognition result of the data collection buried point includes: Obtain the historical reporting status information from the historical data reporting information. The historical reporting status information is generated when the previous historical buried point data triggered reporting before the current moment, and the type of the data collection buried point of the historical buried point data is the buried point type; if the historical reporting status information is abnormal, determine that the status recognition result of the data collection buried point is abnormal; if the historical reporting status information is normal, obtain the reporting moment of the historical buried point data from the historical data reporting information, and determine the status recognition result of the data collection buried point according to the reporting moment; The determining the status recognition result of the data collection buried point according to the reporting moment includes: If the difference between the reporting moment and the current moment is less than the target threshold, determine that the status recognition result of the data collection buried point is abnormal; if the difference between the reporting moment and the current moment is greater than the target threshold, determine that the status recognition result of the data collection buried point is normal.

2. The method according to claim 1, wherein The performing anomaly recognition based on the historical data reporting information to obtain the status recognition result of the data collection buried point includes: Collect the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; Use the target anomaly analysis model to perform anomaly recognition processing based on the terminal status information, the module status information, and the historical reporting status information in the historical data reporting information to obtain at least one status information and the confidence level of each status information; Determine the status recognition result of the data collection buried point according to the at least one status information and the confidence level of each status information.

3. The method according to claim 1, wherein The method further includes: Collect the terminal status information of the local terminal and the module status information of the terminal performance module corresponding to the data collection buried point of the target buried point data; Use the target threshold analysis model to perform threshold analysis based on the terminal status information, the module status information, and the historical reporting status information to obtain at least one threshold and the confidence level of each threshold; Determine the target threshold according to the at least one threshold and the confidence level of each threshold.

4. The method according to claim 1, wherein The method further includes: When the status recognition result is abnormal, perform stop reporting processing on the target buried point data.

5. The method according to claim 4, wherein Establish a buffer area and a first interface in the log saving process. The first interface is used for being called by the first performance module in the user program space, and the log saving process includes a target thread; Establish a target kernel thread, a communication thread, and a second interface in the kernel space. The target kernel thread performs cross-thread communication with the target thread through the communication thread. The second interface is used for being called by a second performance module in the user program space; The stopping reporting process of the target buried point data includes: When the data collection buried point is in the first performance module and the target buried point data is triggered to be reported by the data collection buried point, call the first interface based on the first performance module, and save the target buried point data to the buffer; When the data collection buried point is in the second performance module and the target buried point data is triggered to be reported by the data collection buried point, call the second interface based on the second performance module, and save the target buried point data to the buffer through the cross-thread communication.

6. A control device for reporting buried point data, characterized in that, It includes: A monitoring module, configured to determine the buried point type corresponding to the data collection buried point of the target buried point data when it is monitored that the target buried point data triggers a report; An acquisition module, configured to acquire the historical data reporting information corresponding to the buried point type from the local database; An identification module, configured to perform anomaly identification processing based on the historical data reporting information to obtain the status identification result of the data collection buried point; The performing anomaly identification based on the historical data reporting information to obtain the status identification result of the data collection buried point includes: obtaining historical reporting status information from the historical data reporting information. The historical reporting status information is generated when the previous historical buried point data triggers a report before the current moment, and the type of the data collection buried point of the historical buried point data is the buried point type; if the historical reporting status information is abnormal, determine that the status identification result of the data collection buried point is abnormal; if the historical reporting status information is normal, obtain the reporting moment of the historical buried point data from the historical data reporting information, and determine the status identification result of the data collection buried point according to the reporting moment; wherein, the determining the status identification result of the data collection buried point according to the reporting moment includes: if the difference between the reporting moment and the current moment is less than the target threshold, determine that the status identification result of the data collection buried point is abnormal; if the difference between the reporting moment and the current moment is greater than the target threshold, determine that the status identification result of the data collection buried point is normal; A control module, configured to perform a reporting process on the target buried point data when the status identification result is normal.

7. A storage medium, characterized in that, A computer program is stored thereon. When the computer program is executed by a processor of a computer, the computer is caused to execute the method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, It includes: A memory, storing a computer program; A processor, reading the computer program stored in the memory to execute the method according to any one of claims 1 to 5.

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