CN113886213A

CN113886213A - Program data processing method, device, computer readable storage medium and equipment

Info

Publication number: CN113886213A
Application number: CN202010611462.2A
Authority: CN
Inventors: 钱坤; 郭志伟; 黄思程; 黄为伟; 曾子平; 张泽浩; 陈静; 吕晨欣
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2020-06-29
Filing date: 2020-06-29
Publication date: 2022-01-04

Abstract

The application provides a program data processing method, a program data processing device, a computer readable storage medium and an electronic device; relates to the technical field of computers; acquiring program monitoring information according to information input operation; calling a data acquisition interface to acquire first program data corresponding to the program monitoring information; performing exception screening on the first program data to obtain second program data; and when the input data screening condition is detected, screening the second program data according to the data screening condition to obtain third program data and outputting the third program data. Therefore, by implementing the technical scheme of the application, the correctness of the output program data can be improved through abnormal data screening, and the accuracy of an analysis result obtained when a developer analyzes data is further ensured.

Description

Program data processing method, device, computer readable storage medium and equipment

Technical Field

The present application relates to the field of computer technologies, and in particular, to a program data processing method, a program data processing apparatus, a computer-readable storage medium, and an electronic device.

Background

Before the program is formally brought online, a test board is usually required to be pushed out to a user, so that problems existing in the program can be located according to data fed back when the user uses the test board, and further, the existing problems can be optimized in a targeted manner. Generally, after data fed back by a user is acquired, the data fed back by the user needs to be summarized and analyzed for different detection items (such as page jump speed). However, the data fed back by the user may not be completely correct, and if the developer directly analyzes the data fed back by the user, the correctness of the analysis result is easily affected.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present application and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.

Disclosure of Invention

An object of the present application is to provide a program data processing method, a program data processing apparatus, a computer-readable storage medium, and an electronic device, which can improve the correctness of output program data by screening abnormal data, thereby facilitating to ensure the accuracy of an analysis result obtained when a developer performs data analysis.

Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.

According to an aspect of the present application, there is provided a program data processing method including:

acquiring program monitoring information according to information input operation;

calling a data acquisition interface to acquire first program data corresponding to the program monitoring information;

performing exception screening on the first program data to obtain second program data;

and when the input data screening condition is detected, screening the second program data according to the data screening condition to obtain third program data and outputting the third program data.

According to another aspect of the present application, there is provided a program data processing apparatus including an information acquisition unit, a data acquisition unit, and a data filtering unit, wherein:

an information acquisition unit for acquiring program monitoring information according to an information input operation;

the data acquisition unit is used for calling a data acquisition interface to acquire first program data corresponding to the program monitoring information;

the data screening unit is used for carrying out exception screening on the first program data to obtain second program data;

and the data screening unit is also used for screening the second program data according to the data screening conditions to obtain third program data and outputting the third program data when the input data screening conditions are detected.

In an exemplary embodiment of the present application, the information acquisition unit acquires the program monitoring information according to an information input operation, including:

outputting an information input interface comprising a plurality of types of interaction areas;

when information input operation acting on various types of interaction areas is detected, program monitoring information corresponding to the information input operation is acquired;

the multiple types of interaction areas at least comprise a monitoring index name interaction area, a monitoring index explanation interaction area and a category interaction area to which the monitoring index belongs.

In an exemplary embodiment of the present application, the apparatus further includes a number generation unit and a number presentation unit, wherein:

the number generating unit is used for generating a monitoring number according to the program monitoring information corresponding to the monitoring index name after the information acquiring unit acquires the program monitoring information according to the information input operation;

and the number display unit is used for displaying the monitoring number in the information input interface.

In an exemplary embodiment of the present application, the apparatus further includes a version type obtaining unit, an upload mode determining unit, and a data upload unit, where:

the version type acquisition unit is used for acquiring the version type corresponding to the program to be monitored after the data acquisition unit calls the data acquisition interface to acquire the first program data corresponding to the program monitoring information;

the uploading mode determining unit is used for determining the uploading mode of the first program data according to the version type;

and the data uploading unit is used for uploading the first program data to the data storage system according to the uploading mode.

In an exemplary embodiment of the present application, wherein:

if the version type is an informal version, the data uploading unit uploads the first program data to the data storage system according to an uploading mode, and the method comprises the following steps:

packaging first program data received in a first unit time into a first data packet;

transmitting the first data packet to a data pipeline, so that the data pipeline packs and uploads the first data packet received in the second unit time to a data storage system;

if the version type is a formal version, the data uploading unit uploads the first program data to the data storage system according to an uploading mode, and the method comprises the following steps:

packaging the first program data received in the third unit time into a second data packet;

transmitting the second data packet to the client, so that the client packages and uploads the second data packet received in the fourth unit time to the data storage system;

wherein the first unit time is greater than the second unit time; the third unit time and the fourth unit time are both greater than the first unit time.

In an exemplary embodiment of the present application, the performing exception screening on the first program data by the data screening unit to obtain the second program data includes:

obtaining first program data from a data storage system;

performing exception screening on the first program data according to preset unit time;

and if the screening result contains abnormal outlier data, screening the abnormal outlier data to obtain second program data.

In an exemplary embodiment of the application, the data filtering unit is further configured to perform outlier data filtering on the filtering result according to a specific unit time greater than a preset unit time before the second program data is obtained by filtering the outlier data.

In an exemplary embodiment of the present application, the apparatus further includes an algorithm updating unit, wherein:

and the algorithm updating unit is used for updating the algorithm of the program to be monitored according to the second program data after the data screening unit screens out the abnormal outlier data to obtain the second program data.

In an exemplary embodiment of the present application, the apparatus further includes a data storage unit, wherein:

and the data storage unit is used for inputting the second program data into the asynchronous message sequence after the data screening unit screens out the abnormal outlier data to obtain the second program data, so that the asynchronous message sequence stores the second program data into the database according to the data receiving sequence.

In an exemplary embodiment of the present application, the apparatus further includes a screening condition determining unit, wherein:

a screening condition determining unit configured to determine a data screening condition according to the detected screening condition selecting operation before the data screening unit screens the second program data according to the data screening condition; the data screening condition comprises at least one of a network type, an operator, a time period to be analyzed and data granularity.

In an exemplary embodiment of the present application, the apparatus further includes a data merging processing unit, wherein:

and the data merging processing unit is used for merging the third program data according to the data granularity after the data screening unit screens the second program data according to the data screening condition to obtain the third program data.

In an exemplary embodiment of the present application, the data filtering unit outputs the third program data, including:

converting the third program data into a graph and displaying the graph; and/or the presence of a gas in the gas,

the third program data is represented by a different region in the map and the map is displayed.

According to another aspect of the present application, there is provided an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of any one of the above via execution of the executable instructions.

According to another aspect of the application, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, implements the method of any one of the above.

The exemplary embodiments of the present application may have some or all of the following advantages:

in the program data processing method provided in an example embodiment of the present application, program monitoring information may be acquired according to an information input operation; calling a data acquisition interface to acquire first program data corresponding to the program monitoring information; performing exception screening on the first program data to obtain second program data; and when the input data screening condition is detected, screening the second program data according to the data screening condition to obtain third program data and outputting the third program data. According to the scheme description, on one hand, the accuracy of the output program data can be improved through abnormal data screening, and the accuracy of an analysis result obtained when a developer analyzes data is further guaranteed. On the other hand, the program data required by the user can be screened out according to the personalized requirements of the user, so that the use experience of the user is improved.

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 application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 is a schematic diagram showing an exemplary system architecture to which a program data processing method and a program data processing apparatus according to the embodiments of the present application can be applied;

FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing an electronic device of an embodiment of the present application;

FIG. 3 schematically shows a flow chart of a program data processing method according to an embodiment of the present application;

FIG. 4 schematically illustrates an information input interface diagram according to an embodiment of the present application;

FIG. 5 schematically illustrates a module interaction diagram for uploading first program data to a data storage system according to an embodiment of the present application;

FIG. 6 schematically illustrates a module interaction diagram for uploading first program data to a data storage system according to an uploading mode when a version type is a formal version according to an embodiment of the present application;

FIG. 7 schematically illustrates a module interaction diagram for exception screening of first program data in an embodiment in accordance with the present application;

FIG. 8 schematically shows a flow chart for data redrawing of second program data according to an embodiment of the present application;

FIG. 9 schematically illustrates a data redraw effect diagram according to one embodiment of the present application;

FIG. 10 schematically shows a diagram of a graph in an embodiment according to the present application;

FIG. 11 schematically shows a schematic diagram of a map in an embodiment in accordance with the present application;

FIG. 12 schematically shows a flow chart of a program data processing method according to an embodiment of the present application;

FIG. 13 schematically shows a block diagram of a program data processing method according to an embodiment of the present application;

fig. 14 schematically shows a block diagram of a program data processing apparatus in an embodiment according to the present application.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present application.

Furthermore, the drawings are merely schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

Fig. 1 is a schematic diagram showing a system architecture of an exemplary application environment to which a program data processing method and a program data processing apparatus according to the embodiments of the present application can be applied.

As shown in fig. 1, the system architecture 100 may include one or more of

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few. The

terminal devices

101, 102, 103 may be various electronic devices having a display screen, including but not limited to desktop computers, portable computers, smart phones, tablet computers, and the like. It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.

The program data processing method provided by the embodiment of the application is generally executed by the

terminal device

101, 102 or 103, and accordingly, the program data processing device is generally arranged in the

terminal device

101, 102 or 103. However, it is easily understood by those skilled in the art that the program data processing method provided in the embodiment of the present application may also be executed by the server 105, and accordingly, the program data processing apparatus may also be disposed in the server 105, which is not particularly limited in the exemplary embodiment. For example, in one exemplary embodiment, the server 105 may obtain program monitoring information based on an information input operation; calling a data acquisition interface to acquire first program data corresponding to the program monitoring information; performing exception screening on the first program data to obtain second program data; and when the input data screening condition is detected, screening the second program data according to the data screening condition to obtain third program data and outputting the third program data.

FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.

It should be noted that the computer system 200 of the electronic device shown in fig. 2 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 2, the computer system 200 includes a Central Processing Unit (CPU)201 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)202 or a program loaded from a storage section 208 into a Random Access Memory (RAM) 203. In the RAM 203, various programs and data necessary for system operation are also stored. The CPU 201, ROM 202, and RAM 203 are connected to each other via a bus 204. An input/output (I/O) interface 205 is also connected to bus 204.

The following components are connected to the I/O interface 205: an input portion 206 including a keyboard, a mouse, and the like; an output section 207 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 208 including a hard disk and the like; and a communication section 209 including a network interface card such as a LAN card, a modem, or the like. The communication section 209 performs communication processing via a network such as the internet. A drive 210 is also connected to the I/O interface 205 as needed. A removable medium 211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is mounted on the drive 210 as necessary, so that a computer program read out therefrom is installed into the storage section 208 as necessary.

In particular, according to embodiments of the present application, the processes described below with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 209 and/or installed from the removable medium 211. The computer program, when executed by a Central Processing Unit (CPU)201, performs various functions defined in the methods and apparatus of the present application.

For small programs, performance data such as loading speed, network speed and the like easily and directly influence user retention and conversion. For example, when the loading time is too long, the waiting time of the user is long, which easily affects the user experience. Therefore, before the program is formally brought online, the test board is usually pushed out to the user, so as to locate the problems existing in the program according to the data fed back when the user uses the test board, and further, the existing problems can be optimized in a targeted manner. Generally, after data fed back by a user is acquired, the data fed back by the user needs to be summarized and analyzed for different detection items (such as page jump speed). However, the accuracy of the data acquired by the user in this way cannot be guaranteed, and therefore, how to help the user to personally acquire the required correct data and further improve the analysis efficiency of the user becomes a problem which needs to be solved at present.

In view of the above problems, the present exemplary embodiment provides a program data processing method. The program data processing method may be applied to the server 105, and may also be applied to one or more of the

terminal devices

101, 102, and 103, which is not particularly limited in this exemplary embodiment. Referring to fig. 3, the program data processing method may include the following steps S310 to S340:

step S310: and acquiring program monitoring information according to the information input operation.

Step S320: and calling a data acquisition interface to acquire first program data corresponding to the program monitoring information.

Step S330: and carrying out exception screening on the first program data to obtain second program data.

Step S340: and when the input data screening condition is detected, screening the second program data according to the data screening condition to obtain third program data and outputting the third program data.

By implementing the method shown in fig. 3, the correctness of the output program data can be improved through abnormal data screening, thereby being beneficial to ensuring the accuracy of an analysis result obtained when a developer performs data analysis. In addition, program data required by the user can be screened out according to the personalized requirements of the user, so that the use experience of the user can be improved.

The above steps of the present exemplary embodiment will be described in more detail below.

In step S310, program monitoring information is acquired according to the information input operation.

Specifically, the information input operation may be a key input operation, a voice input operation, a gesture input operation, a hook selection operation, or a handwriting operation acting on the touch screen, and the like, and the embodiment of the present application is not limited; the key-in operation can be an operation that a user taps on an external device (such as a keyboard) connected with the terminal device/server to realize the input of the program monitoring information; the voice input operation can be the operation of voice input after the voice signal acquisition triggering function is started by a user; the gesture input operation can be gesture performance performed by a user in the acquisition process of the camera module, so that the terminal device/server determines text content corresponding to the acquired gesture according to the acquired gesture and determines the text content as program monitoring information; the checking operation can be an option selected by a user from a plurality of options displayed on the information input interface as program monitoring information; the handwriting operation acting on the touch screen can be character handwriting performed in a handwriting interaction area for a user, and the terminal equipment can determine program monitoring information through recognition of character handwriting results. Further, the program monitoring information may be: for the monitoring items of the program to be monitored, one program monitoring information may correspond to one or more monitoring items.

As an optional implementation, acquiring the program monitoring information according to the information input operation includes:

Specifically, program monitoring information corresponding to information input operations acting on different interaction areas is different; the program monitoring information (namely, the monitoring index name) in the monitoring index name interaction region can be page jump time consumption and/or cloud function call time consumption and the like; the program monitoring information (namely, monitoring index interpretation) in the monitoring index interpretation interaction area is used for interpreting the monitoring index name; the program monitoring information in the category interaction area to which the monitoring index belongs (i.e., the category to which the monitoring index belongs) is used for indicating the category to which the name of the monitoring index belongs. In addition, it should be noted that one program to be monitored may correspond to one or more monitoring items, and each monitoring item includes a corresponding monitoring index name, a monitoring index explanation, and a category to which the monitoring index belongs.

Referring to fig. 4, fig. 4 schematically illustrates an information input interface according to an embodiment of the present application. As shown in fig. 4, the information input interface includes a monitoring index name interaction area 401, a monitoring index interpretation interaction area 402, and a category interaction area 403 to which the monitoring index belongs. If an information input operation acting on the monitoring index name interaction area 401 is detected, program monitoring information corresponding to the information input operation can be acquired, and the program monitoring information can be a monitoring index name; if an information input operation acting on the monitoring index interpretation interaction area 402 is detected, program monitoring information corresponding to the information input operation may be acquired, and the program monitoring information may be a monitoring index interpretation; if an information input operation acting on the category interaction region 403 to which the monitoring index belongs is detected, program monitoring information corresponding to the information input operation may be acquired, and the program monitoring information may be a category to which the monitoring index belongs. In addition, after the user inputs the program monitoring information in the monitoring index name interaction region 401, the monitoring index interpretation interaction region 402 and the category interaction region 403 to which the monitoring index belongs, the user can interact with the modification control 404 or the modification control 405 to modify the program monitoring information in the row where the modification control 404 or the modification control 405 is located.

Therefore, by implementing the optional implementation mode, the program monitoring information can be determined through the information input operation, so that program monitoring can be performed according to the program monitoring information, and a monitoring result can be returned to a user, so that the monitoring requirement of the user can be met.

As an optional implementation manner, after acquiring the program monitoring information according to the information input operation, the method further includes:

generating a monitoring number according to the program monitoring information corresponding to the monitoring index name;

and displaying the monitoring number in the information input interface.

Specifically, the monitoring number is used as a unique representation of a monitoring item of the program to be monitored, and the monitoring number may be formed by at least one of numbers, english, chinese, and symbols, which is not limited in the embodiment of the present application. In addition, optionally, the manner of generating the monitoring number according to the program monitoring information corresponding to the monitoring index name may specifically be: determining the number of the program monitoring information corresponding to the monitoring index name according to the preset corresponding relation, and using the number as a monitoring number; or generating a random number as a monitoring number according to the program monitoring information corresponding to the monitoring index name. In addition, optionally, the manner of displaying the monitoring number in the information input interface may be: the mode of displaying the monitoring number in the information input interface may specifically be: and determining a number display area corresponding to the monitoring index name in the information input interface, and displaying the monitoring number corresponding to the monitoring index name in the number display area.

Optionally, after the monitoring number is displayed in the information input interface, the method may further include: and generating a table according to the program monitoring information and the monitoring numbers of the various types of interaction areas and displaying the table. Please refer to the following table, including the header: monitoring serial number, monitoring index name, monitoring index explanation, category to which the monitoring index belongs and operation. And when the user operation acting on the control is detected, the table area corresponding to the control is switched into an editable mode. For example, when a user operation acting on "modify" corresponding to "2003" is detected, at least one corresponding table region of "page jump elapsed time", "user page jump class elapsed time", and "load/render class" is switched to an editable mode, and a user can edit content in the editable mode, thereby implementing change of text information in the table.

It can be seen that, in implementing this alternative embodiment, a corresponding monitoring number can be generated so as to call the data acquisition interface to monitor the corresponding monitoring item in a targeted manner.

In step S320, a data obtaining interface is called to obtain first program data corresponding to the program monitoring information.

Specifically, the first program data may be data generated during use of the program. Optionally, the manner of calling the data obtaining interface to obtain the first program data corresponding to the program monitoring information may specifically be: and calling a data acquisition interface to acquire first program data of the monitoring codes corresponding to the monitoring index names. Further, the data acquisition interface may be a wx. When the monitoring codes are 2003 and 1004, the first program data can be page jump time consumption and cloud function call time consumption; the cloud function can be identified through the logic code, and the database and the cloud storage can be connected through the cloud function. For example, the code for calling the data obtaining interface to obtain the first program data corresponding to the program monitoring information is as follows:

as an optional implementation manner, after the data obtaining interface is called to obtain the first program data corresponding to the program monitoring information, the method further includes:

acquiring a version type corresponding to a program to be monitored;

determining an uploading mode of the first program data according to the version type;

and uploading the first program data to the data storage system according to the uploading mode.

Specifically, the version types corresponding to the program to be monitored may include a formal version and an informal version, different version types correspond to different uploading manners, and the uploading manner of the first program data may be understood as a manner of reporting the first program data to the system. In addition, the data storage system may be a distributed publish-subscribe message system (TDBank), where the TDBank is configured to collect data from a service data source in real time, and distribute the data to a back end in a message subscription manner after preprocessing and distributed message caching. Optionally, after the first program data is uploaded to the data storage system according to the upload mode, the data storage system may perform the following operations: an access layer in the data storage system unifies a data protocol of received first program data; a processing layer in the data storage system carries out preprocessing such as data filtering and data sampling on first program data with unified data protocols; a data storage layer in the data storage system stores the preprocessed first program data.

In addition, optionally, before uploading the first program data to the data storage system according to the uploading manner, the method may further include: determining a data volume dimension corresponding to the first program data, and if the data volume dimension is less than or equal to a preset dimension, executing the uploading mode to upload the first program data to the data storage system; and if the data size dimension is larger than the preset dimension, deleting the first program data to enable the data size dimension to be smaller than or equal to the preset dimension. In addition, the method further comprises the following steps: determining a program to be monitored corresponding to the first program data, acquiring configuration parameters of the program to be monitored, and reading the preset dimensionality from the configuration parameters; the preset dimensions corresponding to different programs to be monitored can be the same or different, and the embodiment of the application is not limited.

Therefore, by implementing the optional implementation mode, the uploading mode corresponding to the program to be monitored can be determined according to the version of the program to be monitored, and the acquisition time lengths of the monitoring results corresponding to different uploading modes are different, so that the use experience of a user is improved.

As an optional implementation manner, if the version type is an informal version, uploading the first program data to the data storage system according to an uploading manner, includes:

if the version type is a formal version, uploading the first program data to the data storage system according to an uploading mode, wherein the uploading mode comprises the following steps:

Specifically, the fourth unit time is greater than the third unit time; the data pipeline is used for realizing the data migration processing process between the systems. In addition, optionally, the manner of packaging the first program data received in the first unit time into the first data packet may specifically be: the first program data received in the first unit time is pre-calculated, so that a first data packet is obtained. Similarly, the manner of packaging the first program data received in the third unit time into the second data packet may specifically be: pre-calculating the first program data received in the third unit time to obtain a second data packet; wherein the data in the first data packet is less than the data in the second data packet. Referring to fig. 5, fig. 5 schematically illustrates a module interaction diagram of uploading first program data to a data storage system according to an embodiment of the present application. As shown in fig. 5, after the version type corresponding to the program to be monitored is obtained, the uploading mode of the first program data may be determined according to the version type. If the version type is an informal version, pre-calculating first program data received in a first unit time to obtain a first data packet; the first data packet is transmitted to the data pipe 501, so that the data pipe 501 uploads the first data packet received in the second unit time to the data storage system 503 in a packet mode. If the version type is a formal version, pre-calculating the first program data received in the third unit time to obtain a second data packet; the second data packet is transmitted to the client 502, so that the client 502 uploads the second data packet received in the fourth unit time to the data storage system 503 in a packet mode.

Referring to fig. 6 on the basis of fig. 5, fig. 6 schematically illustrates module interaction diagram of uploading first program data to a data storage system according to an uploading manner when a version type is a formal version according to an embodiment of the present application. As shown in fig. 6, when the version type is a formal version, the precomputation module 601 may precompute the first program data, and further, the precomputation result is uploaded to the upload module 602 in batch through an upload entry in the upload module 602, so that the upload module 602 uploads the first program data to the data storage system 603, and after the data storage system 603 preprocesses and stores the first program data, the first program data is sent to the abnormal data filtering module 604, so that the abnormal data filtering module 604 performs an abnormal data filtering operation according to the configuration information of the program to be monitored, which is pulled from the precomputation module 601 by the configuration pulling module 605.

Therefore, the optional implementation mode can provide two uploading modes, the corresponding uploading modes are determined based on different version types, when the program to be monitored is an informal version, the uploading time interval can be shortened, the monitoring efficiency is improved, a user can obtain a monitoring result in a shorter time, and the program to be monitored of the informal version can be debugged in a targeted manner according to the monitoring result.

In step S330, the first program data is exception-screened to obtain second program data.

Specifically, the second program data does not include an abnormal value, the abnormal value refers to data in the sample that is significantly deviated from the rest of the observed values, and the abnormal value may include at least one of a missing value, an outlier, and a repeated value, and the embodiment of the present application is not limited.

As an optional implementation, performing exception screening on the first program data to obtain second program data includes:

obtaining first program data from a data storage system;

Specifically, the preset unit time may be a preset time window, and the abnormal outlier data also belongs to the abnormal value.

In addition, optionally, the manner of performing exception screening on the first program data according to the preset unit time may specifically be: carrying out data standardization on first program data in a preset unit time; clustering the standardized first program data to obtain a plurality of cluster clusters; and calculating the mean value point of each cluster, and performing exception screening on the first program data according to the distances (such as cosine distance and Euclidean distance) between other data points in the cluster and the mean value point.

In addition, optionally, before the screening out the abnormal outlier data and obtaining the second program data, the method further includes: abnormal outlier data in the screening results were determined by the Z-score (Z-score) algorithm. The method specifically comprises the following steps: by expression

Calculating a Z-score (i.e., Z) for each first program data in the screening results_i) (ii) a If Z_i|>Z_{Threshold value}Judging the first program data corresponding to the Z score as abnormal outlier data; wherein x is_iIs the ith first program data in the screening results, μ is the average of all first program data in the screening results, σ is the standard deviation of all first program data in the screening results, Z_{Threshold value}A predetermined constant (e.g., 2.5, 3.0, 3.5, etc.). It should be noted that the z-score algorithm is a method for detecting parameter anomaly in a one-dimensional or low-dimensional feature space.

As another optional implementation, performing exception screening on the first program data to obtain second program data includes: obtaining first program data from a data storage system; detecting abnormal values in the first program data according to the box chart and screening the abnormal values by an eliminating method, an interpolation method or a replacement method; and if the screening result contains abnormal outlier data, screening the abnormal outlier data to obtain second program data. The method comprises the steps of deleting an abnormal value, determining the abnormal value as a missing value by an interpolation method, and correcting the abnormal value according to two observed values before and after the abnormal value by a replacement method.

Therefore, by implementing the optional implementation mode, the possibility that abnormal data exists in the first program data can be reduced through two times of abnormal screening, so that the program monitoring effect is improved, and the data output accuracy is improved.

As an alternative embodiment, before the screening of the outlier data to obtain the second program data, the method further comprises: and carrying out abnormal outlier data screening on the screening result according to the specific unit time which is greater than the preset unit time.

Specifically, the screening result may be divided into a plurality of groups of data by a specific unit time, and each group of data may be individually subjected to outlier data screening.

Therefore, by implementing the optional implementation mode, the abnormal outlier data screening can be performed on the screening result in the specific unit time, and the abnormal data screening efficiency is further improved.

As an alternative embodiment, after the screening of the outlier data to obtain the second program data, the method further comprises: and updating the algorithm of the program to be monitored according to the second program data.

Specifically, the method for updating the algorithm of the program to be monitored according to the second program data may specifically be: updating the threshold parameter (i.e., Z above) in the algorithm of the program to be monitored based on the second program data_{Threshold value})。

Referring to FIG. 7, FIG. 7 is a schematic diagram illustrating module interaction for exception screening of first program data in accordance with an embodiment of the present applicationFigure (a). As shown in fig. 7, the first filtering submodule 701 in the abnormal data filtering module 700 can perform abnormal filtering on the first program data by a preset unit time, and transmit the filtering result to the second filtering submodule 702, so that the second filtering submodule 702 obtains an algorithm context corresponding to the first program data according to the data to be monitored corresponding to the first program data, as shown in 703, the algorithm context may be an algorithm context of a program to be monitored 1, an algorithm context of a program to be monitored 2, … …, or an algorithm context of a program to be monitored n, n is a positive integer, each algorithm context includes Z_{Threshold value}Z corresponding to different algorithm contexts_{Threshold value}May be the same or different. The second filtering submodule 702 may be based on Z_{Threshold value}And determining abnormal outlier data in the screening result by using a Z-score (Z-score) algorithm, thereby screening the abnormal outlier data to obtain second program data, and further updating the Z in the algorithm context of the corresponding program to be monitored according to the second program data_{Threshold value}For use in the next screening of anomalous data.

In addition, optionally, after updating the algorithm of the program to be monitored according to the second program data, the method may further include: if the program to be monitored is detected to have a fault, determining a data redrawing mode according to fault time; re-reading the second program data according to the determined data redrawing mode and performing duplicate removal processing on the second program data; further, entering the second program data into the asynchronous message sequence is performed as described below. Specifically, the manner of determining the data redrawing manner according to the failure time may be: and if the failure time is less than or equal to a preset threshold (for example, 4 hours), reading the second program data from the data storage system online, and if the failure time is greater than the preset threshold (for example, 4 hours), reading the second program data from the offline database.

Referring to fig. 8, fig. 8 schematically illustrates a flow chart for data redrawing of second program data according to an embodiment of the present application. As shown in fig. 8, the method includes steps S810 to S840, where:

step S810: and detecting whether the failure time is less than a preset threshold value, if so, executing the step S820, and if not, executing the step S830.

Step S820: the second program data is read online from the data storage system.

Step S830: the second program data is read from the offline database.

Step S840: and performing deduplication processing on the second program data.

Specifically, when detecting that a fault exists in the program to be monitored, it may be detected whether a fault time is smaller than a preset threshold, if the fault time is smaller than the preset threshold, the second program data may be read online from the data storage system, and if the fault time is greater than or equal to the preset threshold, the second program data may be read from the offline database. Furthermore, a character string corresponding to the second program data may be determined, and the second program data corresponding to the same character string may be subjected to deduplication processing, where the character string may be used as a unique representation of the second program data. It should be noted that the data in the offline database can be called while offline. By implementing the method shown in fig. 8, the disaster recovery effect can be improved, and when a fault occurs, the data monitoring effect can be prevented from being affected by acquiring the corresponding data in time. Referring to fig. 9 on the basis of fig. 8, fig. 9 schematically illustrates a data redrawing effect diagram according to an embodiment of the present application. After the data redrawing, the second program data with higher accuracy can be obtained, so that the data monitoring effect can be improved.

Therefore, by implementing the optional implementation mode, abnormal values in the program data can be reduced through multiple abnormal data screens, and the accuracy of data analysis is improved.

As an alternative embodiment, after the screening of the outlier data to obtain the second program data, the method further comprises: the second program data is entered into the asynchronous message sequence such that the asynchronous message sequence stores the second program data in the database in the data receipt order.

Specifically, the database may be a time-series storage database.

Therefore, by implementing the alternative embodiment, data storage can be performed through the asynchronous message sequence, so that the calculated amount can be balanced, explosive growth or cliff-breaking drop of the calculated amount of data can be avoided, and the stability of the system can be improved.

In step S340, when the input data filtering condition is detected, the second program data is filtered according to the data filtering condition to obtain third program data and the third program data is output.

Specifically, the third program data is data satisfying a data screening condition; the third program data may be data for presentation. Optionally, the manner of screening the second program data according to the data screening condition to obtain the third program data may specifically be: and calling the second program data from the database and screening the second program data according to the data screening conditions to obtain third program data.

As an optional implementation, before the screening the second program data according to the data screening condition, the method further includes: determining data screening conditions according to the detected screening conditions; the data screening condition comprises at least one of a network type, an operator, a time period to be analyzed and data granularity.

Specifically, the time period to be analyzed may be used to limit the reporting time of the third program data, and the data granularity may include a time granularity, where the time granularity may be seconds, minutes, or hours, and the like. In addition, the selection operation of the screening condition may be a key-in operation, a voice input operation, a gesture input operation, a pointing operation, or a handwriting operation acting on the touch screen. Optionally, before determining the data screening condition according to the detected screening condition selection operation, the method may further include the following steps: the screening condition selection operation is detected in a condition selection area of a display interface for outputting a graph and/or a map.

Therefore, the optional implementation mode can provide a screening condition limiting function, and the user can select the data screening condition according to the personalized requirement so as to obtain the required third program data, so that the use experience of the user can be improved.

As an optional implementation manner, after the second program data is filtered according to the data filtering condition to obtain the third program data, the method further includes: and merging the third program data according to the data granularity.

For example, the third program data belonging to the same minute interval may be merged according to the data granularity of the minute level. The merged third program data satisfies the data screening condition.

Therefore, by implementing the optional implementation mode, the third program data in the form required by the user can be determined through data merging, and the use experience of the user is further improved.

As an alternative embodiment, outputting the third program data includes:

Specifically, the graph is used for displaying the third program data according to the data screening condition. The map may show the third program data by different regions. Optionally, the manner of representing the third program data by different regions in the map and displaying the map may specifically be: representing the third program data by a different region in the map; calculating a data table corresponding to different regions according to the third program data corresponding to the different regions as graphs corresponding to the different regions; and displaying a map and a graphic.

Referring to fig. 10, fig. 10 schematically illustrates a graph in accordance with an embodiment of the present application. As shown in fig. 10, the user may determine the data filtering condition through the filtering condition selecting operation, and may detect the network type (i.e., all networks), the operator (i.e., operator a and operator B), the time period to be analyzed (i.e., 2020-03-1000: 00 to 2020-03-1023: 59), and the data granularity (i.e., 60-minute granularity) included in the data filtering condition 1010. In addition, the data filtering condition 1010 also includes selection of an operating system, that is, all operations, which are used to indicate that the third program data is all operation data corresponding to the program to be monitored when the program to be monitored is used by the user. In addition, any of the network type, operator, time period to be analyzed, data granularity, and operating system in fig. 10 may be modified through user interaction. Further, the graph 1020 includes two curves representing the operator a and the operator B, respectively, which are generated according to the third program data. In addition, in the graph 1020, the abscissa represents time (ms), the third program data represents time (ms), and the ordinate represents time (ms), and the user can visually see the time-consuming data for each time point corresponding to different operators through the graph shown in fig. 10.

Referring to fig. 11, fig. 11 schematically illustrates a map in accordance with an embodiment of the present application. As shown in fig. 11, the third program data may be represented by different regions in the map, and the third program data may be time-consuming data. If the average value of all the third program data in the area is greater than the preset threshold value, the third program data may be highlighted or labeled by a label, for example, the area in the map may be filled by a preset color. In fig. 11, a data table corresponding to the map is also shown, where the data table includes names of different regions, average time consumption corresponding to each region, and data reporting times corresponding to each region, and since data in the data table corresponds to each region in the map one to one, a user can refer to data in the data table to know region distribution of the third program data, thereby improving user experience.

Therefore, by implementing the optional implementation mode, the third program data can be displayed in different display modes, so that the output intuitiveness of the third program data is improved, and the use experience of a user is improved.

Referring to fig. 12, fig. 12 schematically shows a flow chart of a program data processing method according to an embodiment of the present application. As shown in fig. 12, the method includes steps S1200 to S1220, wherein:

step S1200: and outputting an information input interface comprising a plurality of types of interaction areas, and acquiring program monitoring information corresponding to the information input operation when the information input operation acting on the plurality of types of interaction areas is detected.

Step S1202: and generating a monitoring number according to the program monitoring information corresponding to the monitoring index name, and displaying the monitoring number in an information input interface.

Step S1204: and calling a data acquisition interface according to the monitoring number to acquire first program data corresponding to the program monitoring information.

Step S1206: the method comprises the steps of obtaining a version type corresponding to a program to be monitored, and determining an uploading mode of first program data according to the version type. If the version type is an informal version, executing step S1208; if the version type is a formal version, step S1210 is performed.

Step S1208: and packaging the first program data received in the first unit time into a first data packet, and transmitting the first data packet to a data pipeline, so that the data pipeline packages and uploads the first data packet received in the second unit time to a data storage system.

Step 1210: and packaging the first program data received in the third unit time into a second data packet, and transmitting the second data packet to the client, so that the client can upload the second data packet received in the fourth unit time to the data storage system in a packaging manner. Wherein the first unit time is greater than the second unit time; the third unit time and the fourth unit time are both greater than the first unit time.

Step S1212: and acquiring first program data from the data storage system, and performing exception screening on the first program data according to preset unit time.

Step S1214: and if the screening result has abnormal outlier data, screening the abnormal outlier data of the screening result according to the specific unit time which is greater than the preset unit time, and screening the abnormal outlier data to obtain second program data.

Step S1216: determining data screening conditions according to the detected screening conditions; the data screening condition comprises at least one of a network type, an operator, a time period to be analyzed and data granularity.

Step S1218: and screening the second program data according to the data screening conditions to obtain third program data, and merging the third program data according to the data granularity.

Step S1220: converting the third program data into a graph and displaying the graph; and/or, representing the third program data by a different region in the map and displaying the map.

It should be noted that steps S1200 to S1220 correspond to the steps and the embodiment shown in fig. 3, and for the specific implementation of steps S1200 to S1220, please refer to the steps and the embodiment shown in fig. 3, which is not described herein again.

Therefore, by implementing the method shown in fig. 12, the correctness of the output program data can be improved through abnormal data screening, and the accuracy of the analysis result obtained when the developer performs data analysis can be further ensured. In addition, program data required by the user can be screened out according to the personalized requirements of the user, so that the use experience of the user can be improved.

Referring to fig. 13, fig. 13 schematically shows a block diagram of a program data processing method according to an embodiment of the present application. As shown in fig. 13, the module schematic includes: the monitoring system comprises a basic library 1301, a real-time reporting entry module 1302, a data pipeline module 1303, a stream processing system 1304, a dimension protection module 1305, a data storage system 1306, a logic processing module 1307, an asynchronous message queue module 1308, a time sequence storage database 1309, a configuration calling module 1310, a distributed data warehouse 1311 and a program to be monitored management background 1312.

Specifically, the developer may input the program monitoring information through the to-be-monitored program management background 1312, and then the monitoring program management background 1312 may transmit the program monitoring information to the logic processing module 1307, so that the logic processing module 1307 generates a corresponding monitoring number according to the program monitoring information and feeds the monitoring number back to the monitoring program management background 1312, so as to display the monitoring number to the developer through the monitoring program management background 1312.

Further, the base library 1301 may call a data acquisition interface based on the monitoring number to acquire first program data corresponding to the program monitoring information, if the version type of the first program data is an informal version, the first program data is uploaded to the dimension protection module 1305 by combining with the configuration information, corresponding to the program to be monitored, uploaded by the data pipeline module 1303, and if the dimension protection module 1305 detects that the dimension corresponding to the first program data is not greater than the preset dimension, the first program data is sent to the data storage system 1306; if the version type of the first program data is a formal version, uploading the first program data to the real-time reporting entry module 1302, so that the real-time reporting entry module 1302 forwards the first program data to the dimension protection module 1305, and if the dimension protection module 1305 detects that the dimension corresponding to the first program data is not greater than the preset dimension, sending the first program data to the data storage system 1306; the configuration information uploaded by the data pipeline module 1303 may be obtained by calling from the client through the configuration calling module 1310.

In turn, data storage system 1306 may send the first program data to stream processing system 1304, such that stream processing system 1304 performs two-tier exception data screening on the first program data and sends the results of the screening (i.e., the second program data) to logical processing module 1307. Logic processing module 1307 may send the second program data to asynchronous message queue module 1308 to cause message queue module 1308 to store the second program data in chronological storage database 1309 in the order in which the data was received.

When detecting a data screening condition input by a developer through the program management background 1312 to be monitored, the logic processing module 1307 may obtain second user data belonging to a receiving time period corresponding to the data screening condition from the time-series storage database 1309, and screen the second program data according to the data screening condition to obtain third program data; further converting the third program data into a graph and displaying the graph, and/or representing the third program data through different regions in the map and displaying the map; the graphs and/or maps are shown by the to-be-monitored-program management backend 1312.

The distributed data warehouse 1311 is used to store data processing results in other modules in fig. 13 and perform data checking to ensure that data calculation of the module is correct.

Therefore, by implementing the module schematic diagram shown in fig. 13, the correctness of the output program data can be improved through abnormal data screening, and the accuracy of the analysis result obtained when the developer performs data analysis can be further ensured. In addition, program data required by the user can be screened out according to the personalized requirements of the user, so that the use experience of the user can be improved.

Further, in the present exemplary embodiment, a program data processing apparatus is also provided. Referring to fig. 14, the program data processing apparatus 1400 may include an information acquisition unit 1401, a data acquisition unit 1402, and a data filtering unit 1403, wherein:

an information acquisition unit 1401 for acquiring program monitoring information according to an information input operation;

a data obtaining unit 1402, configured to invoke a data obtaining interface to obtain first program data corresponding to the program monitoring information;

a data screening unit 1403, configured to perform exception screening on the first program data to obtain second program data;

the data filtering unit 1403 is further configured to filter the second program data according to the data filtering condition when the input data filtering condition is detected, obtain third program data, and output the third program data.

Therefore, by implementing the device shown in fig. 14, the correctness of the output program data can be improved through abnormal data screening, and the accuracy of the analysis result obtained when a developer performs data analysis can be further ensured. In addition, program data required by the user can be screened out according to the personalized requirements of the user, so that the use experience of the user can be improved.

In an exemplary embodiment of the present application, the information acquisition unit 1401 acquires program monitoring information according to an information input operation, and includes:

In an exemplary embodiment of the present application, the apparatus further includes a number generation unit (not shown) and a number presentation unit (not shown), wherein:

a number generation unit configured to generate a monitoring number according to the program monitoring information corresponding to the monitoring index name after the information acquisition unit 1401 acquires the program monitoring information according to the information input operation;

In an exemplary embodiment of the present application, the apparatus further includes a version type obtaining unit (not shown), an uploading manner determining unit (not shown), and a data uploading unit (not shown), wherein:

the version type acquiring unit is used for acquiring the version type corresponding to the program to be monitored after the data acquiring unit 1402 calls the data acquiring interface to acquire the first program data corresponding to the program monitoring information;

In an exemplary embodiment of the present application, wherein:

In an exemplary embodiment of the present application, the data filtering unit 1403 performs exception filtering on the first program data to obtain the second program data, including:

obtaining first program data from a data storage system;

In an exemplary embodiment of the present application, the data filtering unit 1403 is further configured to perform the outlier screening on the filtering result according to a specific unit time greater than the preset unit time before the outlier screening is performed to obtain the second program data.

In an exemplary embodiment of the present application, the apparatus further includes an algorithm updating unit (not shown), wherein:

and an algorithm updating unit, configured to update the algorithm of the program to be monitored according to the second program data after the data screening unit 1403 screens out the abnormal outlier data to obtain the second program data.

In an exemplary embodiment of the present application, the apparatus further includes a data storage unit (not shown), wherein:

a data storage unit, configured to, after the data screening unit 1403 screens out the abnormal outlier data to obtain second program data, input the second program data into the asynchronous message sequence, so that the asynchronous message sequence stores the second program data in the database according to the data receiving order.

In an exemplary embodiment of the present application, the apparatus further includes a screening condition determining unit (not shown), wherein:

a screening condition determining unit for determining a data screening condition according to the detected screening condition selecting operation before the data screening unit 1403 screens the second program data according to the data screening condition; the data screening condition comprises at least one of a network type, an operator, a time period to be analyzed and data granularity.

In an exemplary embodiment of the present application, the apparatus further includes a data merging processing unit (not shown), wherein:

and a data merging processing unit, configured to merge the third program data according to the data granularity after the data filtering unit 1403 filters the second program data according to the data filtering condition to obtain the third program data.

In an exemplary embodiment of the present application, the data filtering unit 1403 outputs the third program data, which includes:

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the program data processing method described above for details which are not disclosed in the embodiments of the apparatus of the present application, since the respective functional modules of the program data processing apparatus of the exemplary embodiment of the present application correspond to the steps of the exemplary embodiment of the program data processing method described above.

As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method described in the above embodiments.

It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.

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

It will be understood that the present application 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 application is limited only by the appended claims.

Claims

1. A program data processing method, comprising:

2. The method of claim 1, wherein obtaining program monitoring information based on information input operations comprises:

when the information input operation acting on the various types of interaction areas is detected, program monitoring information corresponding to the information input operation is acquired;

3. The method of claim 2, wherein after obtaining the program monitoring information according to the information input operation, the method further comprises:

and displaying the monitoring number in the information input interface.

4. The method according to claim 1, wherein after calling a data acquisition interface to acquire the first program data corresponding to the program monitoring information, the method further comprises:

acquiring a version type corresponding to a program to be monitored;

and uploading the first program data to a data storage system according to the uploading mode.

5. The method of claim 4, wherein:

if the version type is an informal version, uploading the first program data to a data storage system according to the uploading mode, wherein the uploading mode comprises the following steps:

packaging the first program data received in a first unit time into a first data packet;

transmitting the first data packet to a data pipeline, so that the data pipeline uploads the first data packet received in a second unit time to the data storage system in a packaging manner;

if the version type is a formal version, uploading the first program data to a data storage system according to the uploading mode, wherein the uploading mode comprises the following steps:

packaging the first program data received in a third unit time into a second data packet;

transmitting the second data packet to a client, so that the client uploads the second data packet received in a fourth unit time to the data storage system in a packaging manner;

6. The method of claim 4, wherein exception screening the first program data to obtain second program data comprises:

obtaining the first program data from the data storage system;

performing exception screening on the first program data according to a preset unit time;

7. The method of claim 6, wherein prior to screening out the outlier outliers resulting in second program data, the method further comprises:

and screening abnormal outlier data of the screening result according to the specific unit time which is greater than the preset unit time.

8. The method of claim 6, wherein after screening out the outlier outliers resulting in second program data, the method further comprises:

and updating the algorithm of the program to be monitored according to the second program data.

9. The method of claim 6, wherein after screening out the outlier outliers resulting in second program data, the method further comprises:

inputting the second program data into an asynchronous message sequence such that the asynchronous message sequence stores the second program data in a database in a data reception order.

10. The method of claim 1, wherein prior to screening the second program data according to the data screening conditions, the method further comprises:

determining the data screening conditions according to the detected screening condition selection operation; the data screening condition comprises at least one of a network type, an operator, a time period to be analyzed and data granularity.

11. The method of claim 10, wherein after filtering the second program data according to the data filtering condition to obtain third program data, the method further comprises:

and merging the third program data according to the data granularity.

12. The method of claim 1, wherein outputting the third program data comprises:

and representing the third program data by different regions in a map and displaying the map.

13. A program data processing apparatus, characterized by comprising:

the data screening unit is further configured to screen the second program data according to the data screening condition when the input data screening condition is detected, obtain third program data, and output the third program data.

14. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1-12.

15. An electronic device, comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the method of any of claims 1-12 via execution of the executable instructions.