CN110716848A - Data collection method and device, electronic equipment and storage medium - Google Patents
Data collection method and device, electronic equipment and storage medium Download PDFInfo
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- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3438—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment monitoring of user actions
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- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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Abstract
The application discloses a data collection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring target data collected based on the embedded point information, wherein the target data comprises a field name and a value corresponding to the field name; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform. And capturing corresponding data through the buried point information, and directly reporting the data to a data statistics platform to provide basic data support for data statistics and data analysis.
Description
Technical Field
The present application relates to the field of big data, and more particularly, to a data collection method and apparatus, an electronic device, and a storage medium.
Background
With the continuous development of internet technology, various websites and APPs have come to the fore, and users can realize various functions through the websites or APPs. When a user uses a website or an APP interactively, a large amount of data can be generated, and the data are important bases for continuously improving the user experience of various websites and APPs, so that the data are collected and analyzed very importantly.
In the system based on iOS and android, respective statistical requirements exist, statistical analysis can be carried out on the behaviors of the user, and flutter is used as a cross-platform language of a Google open source and has the characteristics of good experience and high development efficiency when used for developing APP. However, in APP developed based on flutter language, without flutter's statistics on relevant data collection, these data cannot be collected.
Disclosure of Invention
The application provides a data collection method, a data collection device, electronic equipment and a storage medium, which are used for collecting and analyzing APP data based on flute to improve the problems.
In a first aspect, an embodiment of the present application provides a data collection method, where the method includes: acquiring target data collected based on the embedded point information, wherein the target data comprises a field name and a value corresponding to the field name; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform.
In a second aspect, an embodiment of the present application provides a data collection apparatus, including: the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring target data collected based on embedded point information, and the target data comprises field names and values corresponding to the field names; the generating module is used for generating the field name and the value corresponding to the field name into a reporting task according to a preset rule; the adding module is used for adding the generated reporting task into a waiting queue and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and the reporting module is used for reporting the reporting tasks in the reporting queue to a data statistics platform.
In a third aspect, an embodiment of the present application provides an electronic device, which includes one or more processors; a memory; one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method as applied to an electronic device, as described above.
In a fourth aspect, the present application provides a computer-readable storage medium having a program code stored therein, wherein the program code performs the above method when running.
According to the data collection method and device, the electronic equipment and the storage medium, target data collected based on the embedded point information are obtained, and the target data comprise field names and values corresponding to the field names; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting tasks into a waiting queue, waiting for the reporting from the waiting queue to the reporting queue, and reporting the reporting tasks in the reporting queue to a data statistics platform. And capturing corresponding data through the buried point information, and reporting the data to a data statistics platform to provide basic data support for data statistics and data analysis.
These and other aspects of the present application will be more readily apparent from the following description of the embodiments.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a flowchart of a data collection method provided by an embodiment of the present application.
Fig. 2 shows a flow chart of a data collection method provided by another embodiment of the present application.
Fig. 3 shows a flow chart of a data collection method provided by another embodiment of the present application.
Fig. 4 shows a flow chart of part of the steps of the data collection method provided on the basis of the embodiment provided in fig. 3.
Fig. 5 is a flow chart illustrating a data collection method according to still another embodiment of the present application.
FIG. 6 is a functional block diagram of a data collection device according to an embodiment of the present application.
Fig. 7 shows a block diagram of an electronic device for executing a data collection method according to an embodiment of the present application.
Fig. 8 illustrates a storage medium provided in an embodiment of the present application and used for storing or carrying program codes for implementing a data collection method according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
With the continuous development of the internet, more and more APPs enter the life of a user, and the user can realize various functions by using the APPs so as to meet the daily life or entertainment requirements. When the user uses the APPs, a large amount of behavior data can be generated, and based on the behavior data, the behavior data can be used as a basis for updating iteration of the APPs, or a new product can be developed according to the behavior data of the user so as to meet the requirements of the user.
In the iOS or android system, respective statistical requirements exist, statistical analysis can be performed on behavior data of a user, flutter is used as a cross-platform language of a Google open source for developing APP, the cross-platform language has the characteristics of good experience and high development efficiency, the flutter is used for developing corresponding APP and is also used by a large number of developers, however, in the application developed by flutter, the behavior data of the user also needs to be collected and counted, and data support is provided for subsequent development.
As an implementation manner, in the hybrid engineering of flutter, when the behavior data is collected and counted, the behavior data may be returned to the APP in a plug-in manner for statistical reporting, but this manner is more performance-consuming in transmitting and requesting data.
Therefore, the inventor proposes a data collection method in the embodiment of the present application, to obtain target data collected based on the buried point information, where the target data includes a field name and a value corresponding to the field name; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform. Data are transmitted back without using a plug-in mode, performance loss is avoided, corresponding data are captured through the embedded point information, and the data are reported to a data statistics platform, so that basic data support is provided for data statistics and data analysis.
The following will describe embodiments of the present application in detail.
Flutter can quickly build applications on iOS and Android. The frame of the Flutter is divided into three layers including Framework, Engine and Embedder; the Framework is realized by using a Dart language, the Engine is realized by using C + +, and the Framework mainly comprises Skia, Dart and Text; embedders are an embedding layer, through which Flutter is embedded into each platform, and the main work of the embedders includes rendering Surface setting, thread setting and the like. Based on flutter, application programs can be developed to realize various functions, and in the application programs developed based on flutter, behavior data generated by the use of users also need to be collected and reported to a data statistics platform to provide basic data support for data statistics and data analysis. Referring to fig. 1, an execution body of a processing flow described in this embodiment may be an electronic device, and is configured to collect and report behavior data generated when a user uses a flutter-based application program. The method comprises the following steps:
step S110, acquiring target data collected based on the buried point information, where the target data includes a field name and a value corresponding to the field name.
A buried point is a common data collection method that captures, processes, and transmits specific user behaviors or events. The method mainly monitors events in the running process of the software application, and judges and captures the events when the events needing attention occur. The method for embedding points can be code embedding points, visual embedding points and non-embedding points. The code embedding refers to adding some codes to a webpage or an APP, reporting data when a user triggers a corresponding behavior, and the APP can also be called a Software Development Kit (SDK); the visual embedded point is connected with equipment configuration events through a management data statistics platform by using a visual interaction means, and then data is collected according to the events; the non-embedded point means that after a developer collects the SDK in an integrated mode, the SDK directly starts to capture and monitor all behaviors of the user in the application and reports all the behaviors, and the developer does not need to add extra codes.
Therefore, after the point is embedded in the webpage or the APP, in the using process of the user, data corresponding to the embedded point information can be collected according to the embedded point information in advance to serve as target data, namely, the data need to be reported to a data statistics platform for further analysis. The target data may include a plurality of field names and values corresponding to the field names. For example, the time length of the user watching the game video, which needs to be reported, may be obtained based on the buried point information, and when the user watches the video through interaction, the user basic information, such as the user id (uid) and other information, and the video information, such as the total time length, the video link, the video name and other information, may be obtained. If the video link of the video information acquired at the moment is https:// www.youtube.com/, the corresponding field name in the target data is the video link, and the value corresponding to the field name is https:// www.youtube.com/.
The field names and the values corresponding to the field names in the acquired target data are related to the buried point information, and if there is a large amount of data corresponding to the buried point information, the acquired target data may include a plurality of field names and values corresponding to the field names.
And step S120, generating a reporting task according to the field name and the value corresponding to the field name according to a preset rule.
After the target data is acquired, the target data needs to be reported to a data statistics platform for data analysis, and the acquired target data may include a plurality of field names and values corresponding to the field names. The reporting tasks can be generated by the fields and the values corresponding to the field names according to preset rules.
The preset rules comprise shorthand rules and splicing rules, and the shorthand rules can be rules for shorthand of the field names so as to control the size of bytes in the generated report task.
In some embodiments, the abbreviation rule may be an abbreviation symbol defining a field name, and the field name is represented by the abbreviation symbol, so as to reduce the number of bytes in the reporting task. In other embodiments, if there is specific data in the reporting task, the specific data may be understood as that in the reporting task reported to the data statistics platform, a data statistics platform person may want to obtain some specific field names and values corresponding to the specific field names, however, when actual data is obtained, the values corresponding to the specific field names may not be obtained, which indicates that even if there is the specific field name in the reporting task, but there is no value corresponding to the specific field name, the specific field name may be deleted, so as to reduce the number of bytes in the reporting task.
The splicing rule is to splice the field names and the values corresponding to the field names into a reporting task so as to associate the obtained field names with the values of the field names, and when a plurality of field names and the values corresponding to the field names exist, to splice each field name and the values corresponding to the field names, to generate the reporting task to report to the data statistics platform.
Therefore, the obtained target data, namely the field name and the value corresponding to the field name, can be generated into a reporting task according to the preset rule, so that the reporting task is reported to a data statistics platform.
Step S130, adding the generated reporting task into the waiting queue, and waiting for the reporting from the waiting queue to the reporting queue.
And step S140, reporting the reporting tasks in the reporting queue to a data statistics platform.
The reporting task is generated according to a preset rule by the field name in the acquired target data and the value corresponding to the field name, and the reporting task comprises all contents of the acquired target data. When the reporting task is reported to the data statistics platform, the target data is also reported to the data statistics platform on the reporting task.
When reporting the reporting task to the data statistics platform, in order to prevent the reporting process from occupying too much resources, two queues may be used for processing, and both queues may be first-in first-out queues including a first-in first-out reporting task. Specifically, the two queues may be a reporting queue and a waiting queue, after the reporting task is generated, the reporting task may be added to the waiting queue, wait for the reporting from the waiting queue to the reporting queue, and report the reporting task in the reporting queue to the data statistics platform, so that the reporting task may be moved from the waiting queue to the reporting queue until all the reporting tasks in the two queues are reported successfully. Therefore, the collected target data can be reported to the data statistics platform through the two queues, so that the data statistics platform can conveniently perform data analysis according to the target data, and basic data support is provided for data statistics and data analysis.
According to the data collection method, target data collected based on the buried point information are obtained, and the target data comprise field names and values corresponding to the field names; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform. In the embodiment of the application, corresponding data is captured through the embedded point information, and the data is directly reported to the data statistics platform, so that basic data support is provided for data statistics and data analysis.
Referring to fig. 2, another embodiment of the present application provides a data collection method, and the process of generating a reporting task is described in detail based on the previous embodiment. Specifically, the method may include:
step S210, obtaining target data collected based on the buried point information, where the target data includes a field name and a value corresponding to the field name.
Step S210 may refer to corresponding parts of the foregoing embodiments, and will not be described herein again.
And step S220, carrying out abbreviation on the field name according to an abbreviation rule to obtain the abbreviated field name.
When the field name and the value corresponding to the field name are obtained, the field name can be abbreviated according to the abbreviation rule to obtain the abbreviated field name.
As an embodiment, the abbreviations corresponding to the field names may be preset, and the field names may be replaced with the preset abbreviations. For example, if the acquired target data includes a field name link and a value https:// www.youtube.com corresponding to the link, the field name link may be simplified to an abbreviation "l", and the field name of the link may be replaced with the abbreviation "l", so as to control the size of bytes in the reporting task.
As another embodiment, the abbreviation rule may delete a field name for which a value corresponding to the field name is not obtained. For example, a specific field name such as an application id and an interface key are preset, and then, in the obtained target data, there are no field name corresponding to the interface key and no value corresponding to the interface key, the field name "interface key" may be deleted, so as to control the size of bytes in the reporting task.
After the obtained field name is abbreviated according to the abbreviation rule, the abbreviated field name can be obtained, so that the abbreviated field name can be reported as a part of the reporting task. It can be understood that the abbreviated field names can be distinguished from each other, different field names cannot become the same abbreviated field name after being abbreviated by the abbreviated rule, and the specific content of the abbreviated rule can be set according to the actual use and is not limited specifically herein.
And step S230, splicing the abbreviated field names according to the splicing rule to obtain the reporting task.
And splicing the abbreviated field name and the value corresponding to the abbreviated field name according to a splicing rule to obtain a reporting task. The reporting task may be a URL link, and the obtained abbreviated field name and the value corresponding to the abbreviated field name are spliced according to a splicing rule to obtain the URL link, so that all the contents of the obtained target data are included in the generated URL link, that is, the reporting task.
For example, when the time for the user to watch the video is reported, the obtained target data comprises a field name link and a value https:// www.youtube.com/, which corresponds to the link; the field name act and a value herovidieo corresponding to the act; the field name, viewtime, and the value 20190904220556 corresponding to the viewtime; the field name appkey, and the value 6ffb6db7c211b966b735f07c16176f7f corresponding to appkey, the field name from, and the value 12 corresponding to from; the field name to, and the value to corresponding to 30; the field name videotype, and the value mobile Legend corresponding to the videotype. After the field names are abbreviated according to the abbreviation rules, the obtained abbreviated field names and the values corresponding to the field names can be referred to table 1.
TABLE 1
| Abbreviated field name | Value corresponding to field name |
| a | herovideo |
| l | https://www.youtube.com/ |
| v | 20190904220556 |
| k | 6ffb6db7c211b966b735f07c16176f7f |
| f | 12 |
| t | 30 |
| y | mobile legend |
As can be seen from table 1, the field names in the acquired target data are abbreviated by the abbreviation rules, and the abbreviated field names are obtained. And splicing the abbreviated field names according to the splicing rule to obtain a URL link as the reporting task. The abbreviation rules may be set according to actual usage, and are not specifically limited herein.
When reporting the reporting task to the data statistics platform, it is necessary to know the corresponding data statistics platform interface address, i.e. the reporting link, where the reporting link may be preset in the splicing rule. For example, the preset reporting link is http:// ylog. According to the concatenation rule, each field name and a value corresponding to the field name may be concatenated into a URL component, please refer to table 1, where table 1 has a plurality of field names to be reported and values corresponding to the field names, and each field name and the value corresponding to the field name in table 1 may be concatenated into a URL component, for example, "a ═ heroideo" may be a URL component; l-https:// www.youtube.com/can also be a URL component, and so on, and each field name and the value corresponding to the field name in table 1 can be spliced into a URL component, so that a plurality of URL components can be obtained.
Furthermore, the URL link can be spliced by using preset symbols according to the reported link and the obtained URL components. For example, if the reporting link is http:// ylog.hiido.com/j.gif and the URL component is obtained according to the contents in Table 1, then the URL link is http:// ylog.hiido.com/j.gif? a ═ herotide & l ═ https:// www.youtube.com/& v ═ 20190904220556& k ═ 6ffb6db7c211b966b735f07c16176f7f & f ═ 12& t ═ 30& y ═ mobile Legend. And after the URL link is obtained, the URL link can be used as a reporting task to be reported to a data statistics platform.
Step S240, adding the generated reporting task into a waiting queue, and waiting for the generated reporting task to be added from the waiting queue to a reporting queue for reporting;
and step S250, reporting the reporting tasks in the reporting queue to a data statistics platform.
The reporting task comprises the acquired target data, so that the target data can be reported to the data statistics platform. It will be appreciated that multiple reporting tasks may be generated based on the user's behavior. For example, when a user clicks one video to watch, one reporting task can be generated according to the target data acquired by the embedded point information, and when the user clicks another video to watch, another reporting task can be generated according to the target data acquired by the embedded point information. When reporting the generated reporting task, in order to place excessive resources occupied during reporting, the reporting queue and the waiting queue can be used for processing, specifically, the reporting task can be added into the waiting queue, the reporting task in the reporting queue is reported to the data statistics platform after waiting for being added from the waiting queue to the reporting queue, and therefore the reporting task can be moved from the waiting queue to the reporting queue until all the reporting tasks in the two queues are reported successfully. And the performance parameters of the electronic equipment can be acquired when the generated report tasks are reported through the report and wait queue, and the report tasks in the queue are suspended according to the performance parameters, so that the influence on the normal use of the electronic equipment is avoided.
According to the data collection method, target data collected based on the buried point information are obtained, and the target data comprise field names and values corresponding to the field names; according to the abbreviation rules, the field name is abbreviated to obtain the abbreviated field name; splicing the abbreviated field names according to a splicing rule to obtain a reporting task; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform. . In the embodiment of the application, corresponding data is captured through the embedded point information, the reporting task is generated according to the preset rule and reported to the data statistics platform, byte control is performed in the process of generating the reporting task, so that the number of bytes in the reporting task is reduced, the reporting of the reporting task is accelerated, and basic data support is provided for data statistics and data analysis.
Referring to fig. 3, another embodiment of the present application provides a data collection method, and this embodiment focuses on the process of reporting the generated reporting task based on the foregoing embodiment. As shown in fig. 3, the method may include:
step S310, acquiring target data collected based on the buried point information, wherein the target data comprises a field name and a value corresponding to the field name.
Step S320, generating a reporting task according to the field name and the value corresponding to the field name according to a preset rule.
The steps S310 to S320 can refer to the corresponding descriptions of the foregoing embodiments, and are not described herein again.
Step S330, reporting the first reporting task in the reporting queue to a data statistics platform.
In the embodiment of the application, two queues are adopted to report the reporting task. The two queues may be a reporting queue and a waiting queue, and report the reporting tasks in the reporting queue, and the reporting tasks in the waiting queue wait for reporting through the reporting queue.
After the field names and the values corresponding to the field names are generated into reporting tasks according to preset rules, the reporting tasks can be added into corresponding queues before a first reporting task in the reporting queue is reported to a data statistics platform. Referring to fig. 4, a process of adding a reporting task to a corresponding queue is shown, and specifically, the method includes the contents of steps S331 to S334.
And step S331, acquiring the generated report task.
After the field name and the value corresponding to the field name are generated into a reporting task according to a preset rule, the generated reporting task can be acquired, and when the reporting task is acquired, the reporting task needs to be added into a reporting queue or a waiting queue to report the reporting task. Since there are two queues, it is therefore necessary to determine whether to add the generated reporting task into the reporting queue or the waiting queue.
Step S332, judging whether a reporting task exists in the reporting queue; if yes, go to step S333; if not, go to step S334.
Step S333, adding the generated reporting task to the waiting queue for waiting to be reported.
Step S334, add the generated reporting task to the reporting queue to perform reporting.
When the generated reporting task is received, if the reporting task is added to a reporting queue, reporting the reporting task; and if the reporting task is added to the waiting queue, waiting for reporting. Therefore, whether the reporting task exists in the reporting queue or not can be judged, if the reporting task exists in the reporting queue, the reporting task is reported, and the generated reporting task can be added into the waiting queue to wait for reporting. If there is no reporting task in the reporting queue, that is, the reporting queue is empty, the generated reporting task may be added to the reporting queue for reporting.
Step S340, judging whether the first reporting task is reported successfully, if so, executing step S350; if not, go to step S360.
When reporting the reporting tasks in the reporting queue, the reporting task may fail under the condition of bad network due to the influence of the network environment. If the reporting of one reporting task fails, which indicates that the data statistics platform does not receive the reporting task, the data carried in the reporting task cannot be acquired, thereby affecting the statistics and analysis of the data statistics platform. Therefore, the reporting condition of the reporting task can be monitored, and when the reporting task fails to report, the step S360 is executed; and executing the step S350 when the reporting task is successfully executed.
When reporting the reporting tasks in the reporting queue, the first reporting task in the reporting queue may be acquired, and the first reporting task is reported to the data statistics platform. If the first reporting task is not successfully reported, the first reporting task needs to be reported again, and if the first reporting task is successfully reported, the next reporting task can be reported. It is thus necessary to determine whether the first reporting task is reported successfully.
As an implementation manner, when a reporting task is reported to a data statistics platform, and the reporting task is reported successfully, a success identifier fed back by the data statistics platform can be received to indicate that the reporting task is reported successfully; when the reporting of the reporting task fails, a failure identifier fed back by the data statistics platform can be received to represent that the reporting of the reporting task fails. Therefore, whether the reporting task is reported successfully or not can be determined according to the success identification or the failure identification fed back by the data statistics platform.
As another embodiment, it may be determined whether a successful identifier fed back by the data statistics platform is received within a preset time after the first reporting task is reported; if the success identifier is received, the first reporting task is considered to be reported successfully; if the success identifier is not received, it may be considered that the first reporting task fails to report.
The required reporting time is different for the reporting tasks with different sizes, and therefore the reporting tasks with different sizes correspond to different preset times. The corresponding relation between the size of the reporting task and the reporting time can be preset. The size of the reporting task and the corresponding reporting time can be counted for many times in the reporting process, and the relationship between the reporting time and the size of the reporting task can be obtained according to a large amount of data. For example, the reporting time is y, and the reporting task size is x; the relation between the reporting time and the reporting task size obtained according to a large amount of data statistics is y ═ k × x, wherein x is a known number, so that the reporting time required by the first reporting task can be determined according to the relation between the reporting time and the reporting task size, and the reporting time is used as the preset time after the first reporting task is reported. If the size of the first reporting task is a, the corresponding preset time is ka; the size of the first reporting task is b, and the corresponding preset time is kb.
Step S350, deleting the first reporting task from the reporting queue, and executing step S340 with the next reporting task as the first reporting task.
If it is determined that the first reporting task is successfully reported, indicating that the data statistics platform has received the target data in the first reporting task, the first reporting task that is successfully reported may be deleted from the reporting queue, and a second reporting task in the reporting queue may be obtained, where after the first reporting task that is successfully reported is deleted, the second reporting task becomes a new first reporting task of the reporting queue. Meanwhile, after the first reporting task which is successfully reported is deleted from the reporting queue, the first reporting task in the waiting queue can be obtained, and the first reporting task in the waiting queue is moved to the tail of the reporting queue. And reporting the reporting tasks in the reporting queue in sequence. Therefore, a new first reporting task can be reported, so that the step of judging whether the first reporting task is reported successfully is continuously executed, and all the reporting tasks in the reporting queue and the waiting queue can be reported.
Step S360, adding the first reporting task to the tail of the waiting queue, deleting the first reporting task from the reporting queue, taking the next reporting task as the first reporting task, and executing step S340.
If the first reporting task is judged not to be successfully reported, the data statistics platform is indicated not to receive the target data in the first reporting task, and the first reporting task can be reported again in order to avoid data loss.
As an implementation method, after the reporting of the first reporting task fails, in order to avoid affecting the reporting of other reporting tasks in the reporting queue, the first reporting task may be moved from the reporting queue to the tail of the waiting queue to wait for reporting again. After the first reporting task is removed from the reporting queue, the next reporting task in the reporting queue can be reported to a data statistics platform as the first reporting task. Therefore, the report progress of the subsequent report tasks is prevented from being influenced because the report of one report task fails.
When the first reporting task which fails to be reported is moved to the tail of the waiting queue, the first reporting task in the waiting queue can be added to the tail of the reporting queue, and the reporting queue continues to report the first reporting task in the queue to form cyclic reporting, so that all the reporting tasks in the reporting queue and the waiting queue can be reported. When there is no reported task in the reporting queue and the waiting queue, it indicates that there is no reported task that needs to be reported to the data statistics platform, and the reporting can be finished.
When reporting the reporting task, two queues are used to complete the reporting. The processing modes of the reporting tasks in the two queues are different, specifically, the two queues are a reporting queue and a waiting queue, the reporting tasks in the reporting queue are reported, and the reporting tasks in the waiting queue wait for reporting. Because the generated reporting tasks are not added into the reporting queue when the reporting tasks exist in the reporting queue, and the reporting tasks in the waiting queue are moved into the reporting queue only after the reporting tasks in the reporting queue are moved or deleted, the number of the reporting tasks in the reporting queue is controlled, and the condition of overflowing the reporting queue can not occur. However, if many reporting tasks are added to the wait queue, the wait queue may overflow. Therefore, the number of the reported tasks in the waiting queue can be controlled.
All the reporting tasks in the reporting queue and the waiting queue can be backed up and stored in a database, and after the reporting tasks are reported successfully, the reporting tasks are deleted from the database. That is, the reporting tasks stored in the database are the reporting tasks that are not reported, and the reporting tasks that are not reported include the reporting tasks that are waiting to be reported and the reporting tasks that are not reported successfully.
Before adding the reporting tasks to the waiting queue, it may be determined whether the number of reporting tasks in the waiting queue is equal to a preset number, where the preset number is the number of reporting tasks when the waiting queue is full. If the number of the reported tasks in the waiting queue is equal to the preset number, it indicates that the number of the reported tasks in the waiting queue has reached the maximum value, and if there are more reported tasks to be added into the waiting queue, the waiting queue will overflow. Therefore, the first reporting task in the waiting queue can be deleted from the waiting queue, that is, the reporting task at the head of the waiting queue is deleted, and the reporting task which needs to be added into the waiting queue is added to the tail of the waiting queue. After the first reporting task in the waiting queue is deleted, the reporting tasks are added into the waiting queue, and the number in the waiting queue is always maintained at the preset number, so that the reporting tasks cannot overflow.
For the reporting task deleted from the waiting queue, the deleted reporting task cannot be lost due to backup in the database. When the task data in the waiting queue is less than the preset number, the reporting task deleted from the waiting queue may be added to the waiting queue again from the database.
In addition, the reporting tasks in the reporting queue and the waiting queue are backed up, so that the condition that the APP is closed in the reporting process or the reporting task is lost when the electronic equipment is shut down can be prevented, the reporting tasks in the database can be added into the reporting queue or the waiting queue when the APP is started, and the reporting tasks are continuously reported.
Since the flutter is a single thread, there is no multi-thread model, and in order not to block the normal UI thread, asynchronous processing can be implemented using the asynchronous mode Future and sync awake. The method may include monitoring whether execution of an application program corresponding to the target data is finished after the target number is acquired, and if the execution is finished, reporting of the execution data does not affect use of the application program, so that a reporting task is generated by the field name and a value corresponding to the field name according to a preset rule and then the reporting task is reported to a data statistics platform. Specifically, wait and sync asynchronous tasks can be injected into an event loop to realize the asynchronous tasks. For example, when a user watches a video, target data related to the video is acquired, and in order to avoid influencing the normal watching process and related operations of the user, the target data is reported after the running of the video software is finished, so that the normal use of the electronic equipment cannot be influenced in the reporting process of a reporting task.
According to the data collection method, when the reporting tasks are obtained, the reporting tasks are reported to the data statistics platform through the reporting queue and the waiting queue, the number of the reporting tasks in the reporting queue is controlled through the waiting queue, and the reporting queue is prevented from overflowing. And the reporting tasks are backed up in a database mode, so that the reporting tasks can be prevented from being lost while the waiting queue is prevented from overflowing, all the reporting tasks can be reported to a data statistics platform, and basic data support is provided for data statistics and data analysis.
In the process of reporting the task, the running performance of the electronic equipment can be detected in real time, and when the performance of the electronic equipment is abnormal, the reporting is suspended. Specifically, referring to fig. 5, a further embodiment of the present application provides a data collection method, where on the basis of the foregoing embodiment, the embodiment mainly describes processes of suspending reporting and resuming reporting in a process of reporting a reporting task, and the method may include:
step S410, acquiring target data collected based on the buried point information, where the target data includes a field name and a value corresponding to the field name.
Step S420, generating a reporting task according to the field name and the value corresponding to the field name according to a preset rule.
Step S430, add the generated reporting task to the waiting queue, and wait for the reporting task to be added from the waiting queue to the reporting queue.
Step S440, reporting the reporting task in the reporting queue to a data statistics platform.
The steps S410 to S440 can refer to the corresponding parts of the previous embodiments, and are not described herein again.
Step S450, acquiring the performance parameters of the electronic equipment in the process of reporting the task.
In the process of reporting the reporting task, the reporting task and the performance of the electronic equipment are mutually influenced. For example, when the memory occupancy rate of the electronic device is high, the reporting task is continuously reported, which may cause the phenomena of electronic device jamming, heating, etc.; if the current network environment of the electronic device is not good, the reporting task may fail to be reported. Therefore, in the process of reporting the reporting task, the performance parameters of the electronic equipment can be acquired to determine whether the reporting of the reporting task influences the normal use of the electronic equipment or whether the reporting of the reporting task fails in batch.
The performance parameter of the electronic device may be a refresh frequency, a memory occupancy rate and/or a network speed of the currently displayed content of the electronic device.
Step S460, if the performance parameter is within the preset range, suspending reporting the reporting task in the reporting queue.
When the performance parameter of the electronic device is acquired, whether the performance parameter is in a preset range can be determined to determine whether to suspend the reporting task. The performance parameter may be a refresh rate, a memory occupancy rate, or a network speed. The preset range corresponding to each performance parameter can be preset, namely the refresh frequency corresponds to the preset refresh frequency range; the memory occupancy rate corresponds to a preset memory occupancy rate range; the network speed corresponds to a preset network speed range. When the performance parameter is in the corresponding preset range, the reporting task in the reporting queue may affect the normal use of the electronic device, causing phenomena of jamming, heating and the like, or may cause batch reporting failures of the reporting tasks.
As an implementation manner, when one of the performance parameters is obtained, whether the performance parameter is in a corresponding preset range may be determined; if the current time is within the corresponding preset range, the reporting task in the reporting queue is suspended; and if the current parameter is not in the corresponding preset range, acquiring another performance parameter for judgment. It can be understood that, when any one of the obtained refresh frequency, the memory occupancy rate, or the network speed is within the preset range, the reporting task in the reporting queue may be suspended.
As another embodiment, the preset condition may be that, when the acquired performance parameters are all in the corresponding preset ranges, the reporting task in the reporting queue is suspended. That is to say, the refresh frequency, the memory occupancy rate and the network speed may be obtained at the same time, and when the refresh frequency is within the preset refresh frequency range, the memory occupancy rate is within the preset memory occupancy rate range, and the network speed is within the preset network speed range, the reporting task in the reporting queue is suspended.
When the reporting of the reporting task in the reporting queue is suspended, the reporting task can be kept added into the waiting queue or the database, and only the reporting task in the reporting queue is suspended. When the performance parameter is not within the preset range, the reporting task reported in the reporting queue may be resumed, specifically, when the performance parameter of the electronic device is not within the corresponding preset range, the reporting may be resumed.
As an implementation manner, when the refresh frequency, the memory occupancy rate, and the network speed are not within the preset range, the reporting may be resumed. As another embodiment, whether to resume reporting may be determined according to the reason for suspending reporting. For example, if the reporting task is suspended because the refresh frequency is within the preset range, the refresh frequency can be continuously acquired, and when the refresh frequency is not within the preset range, the reporting of the reporting task is resumed. Similarly, if the reporting task is suspended because the network speed is within the preset range, the network speed can be continuously obtained, and the reporting of the reporting task is resumed when the network speed is not within the preset range.
According to the data collection method, the performance parameters in the process of reporting the reporting tasks are obtained, and when the performance parameters are within the preset range, the reporting tasks are still reported, so that the normal use of the electronic equipment can be influenced or the reporting failure of the batch reporting tasks can occur, the reporting tasks reported in the reporting queue can be suspended, and the influence on the use of the electronic equipment and the reporting failure of the batch reporting tasks can be avoided; when the performance parameter is not in the preset range, the reporting of the reporting task in the reporting queue can be resumed, so that the reporting task can be reported to the data statistics platform, basic data support is provided for data statistics and data analysis, meanwhile, the normal use of the electronic equipment is prevented from being influenced, and the use experience of a user is considered.
Referring to fig. 6, a data collection apparatus 500 according to an embodiment of the present application is shown, where the data collection apparatus 500 includes an obtaining module 510, a generating module 520, an adding module 530, and a reporting module 540.
An obtaining module 510, configured to obtain target data collected based on the embedded point information, where the target data includes a field name and a value corresponding to the field name; a generating module 520, configured to generate a reporting task according to a preset rule by using the field name and a value corresponding to the field name; an adding module 530, configured to add the generated reporting task to a waiting queue, and wait for the generated reporting task to be added from the waiting queue to a reporting queue for reporting; and a reporting module 540, configured to report the reporting task in the reporting queue to a data statistics platform.
Further, the preset rules include field name abbreviation rules and splicing rules, and the generating module 520 is further configured to perform abbreviation on the field names according to the abbreviation rules to obtain abbreviated field names; and splicing the abbreviated field names according to the splicing rule to obtain the reporting task.
Further, a reporting link is preset, and the generating module is further configured to splice the reporting link, the abbreviated field name, and a value corresponding to the field name into the reporting task.
Further, the adding module 530 is further configured to add the generated reporting task to the waiting queue; the reporting module 540 is further configured to report the first reporting task in the reporting queue to a data statistics platform; judging whether the first reporting task is reported successfully; if so, deleting the first reporting task from the reporting queue, taking the next reporting task as the first reporting task, and acquiring the reporting task from the waiting queue and adding the reporting task to the reporting queue; and if not, adding the first reporting task to the tail of the waiting queue, and deleting the first reporting task from the reporting queue.
Further, before adding the generated reporting task to the waiting queue, the reporting module 540 is further configured to determine whether a reporting task exists in the reporting queue; if so, adding the generated reporting task to the waiting queue for waiting to be reported; and if not, adding the generated reporting task into the reporting queue to carry out reporting.
Further, a database is preset, where the database is configured to backup all unreported reporting tasks in the reporting queue and the waiting queue, and the reporting module 530 is further configured to delete a first reporting task in the waiting queue from the waiting queue before adding a reporting task to the waiting queue, if the number of reporting tasks in the waiting queue is equal to a preset number, where the preset number is the number of reporting tasks when the waiting queue is full; and when the number of the reported tasks in the waiting queue is less than the preset number, taking out the reported tasks which are not reported from the database and adding the reported tasks into the waiting queue.
Further, the apparatus 500 further includes a detection module, where the detection module is configured to obtain performance parameters of the electronic device in a process of reporting the reporting task in the reporting queue, where the performance parameters include a refresh frequency, a memory occupancy rate, and/or a network speed; and when the performance parameter is in a preset range, suspending the report of the report tasks in the report queue.
Further, after the target data is obtained, if it is monitored that the execution of the application program corresponding to the target data is finished, the generating module 520 executes a step of generating the field name and the value corresponding to the field name according to a preset rule to report a task.
It should be noted that, as will be clear to those skilled in the art, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In summary, the data collection method provided by the present application obtains target data collected based on the embedded point information, where the target data includes a field name and a value corresponding to the field name; generating a reporting task by the field name and a value corresponding to the field name according to a preset rule; adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting; and reporting the reporting tasks in the reporting queue to a data statistics platform. And capturing corresponding data through the buried point information, and directly reporting the data to a data statistics platform to provide basic data support for data statistics and data analysis.
In the several embodiments provided in the present application, the coupling or direct coupling or communication connection between the modules shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or modules may be in an electrical, mechanical or other form.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
Referring to fig. 7, a block diagram of an electronic device according to an embodiment of the present application is shown. The electronic device 600 may be a smart phone, a tablet computer, an electronic book, or other electronic devices capable of running an application. The electronic device 600 in the present application may include one or more of the following components: a processor 610, a memory 620, and one or more applications, wherein the one or more applications may be stored in the memory 620 and configured to be executed by the one or more processors 610, the one or more programs configured to perform the methods as described in the aforementioned method embodiments.
The processor 610 may include one or more processing cores. The processor 610 interfaces with various components throughout the electronic device 600 using various interfaces and circuitry to perform various functions of the electronic device 600 and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 620 and invoking data stored in the memory 620. Alternatively, the processor 610 may be implemented in hardware using at least one of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 610 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing display content; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 610, but may be implemented by a communication chip.
The Memory 620 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). The memory 620 may be used to store instructions, programs, code sets, or instruction sets. The memory 620 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The data storage area may also store data created during use by the electronic device 600 (e.g., phone books, audio-visual data, chat log data), and so forth.
Referring to fig. 8, a block diagram of a computer-readable storage medium according to an embodiment of the present application is shown. The computer-readable storage medium 700 has stored therein program code that can be called by a processor to execute the methods described in the above-described method embodiments.
The computer-readable storage medium 700 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer-readable storage medium 700 includes a non-transitory computer-readable storage medium. The computer readable storage medium 700 has storage space for program code 710 to perform any of the method steps of the method described above. The program code can be read from or written to one or more computer program products. The program code 710 may be compressed, for example, in a suitable form.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not necessarily depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (11)
1. A data collection method applied to an electronic device, the method comprising:
acquiring target data collected based on the embedded point information, wherein the target data comprises a field name and a value corresponding to the field name;
generating a reporting task by the field name and a value corresponding to the field name according to a preset rule;
adding the generated reporting task into a waiting queue, and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting;
and reporting the reporting tasks in the reporting queue to a data statistics platform.
2. The method of claim 1, wherein the preset rules include field name abbreviation rules and concatenation rules, and the generating the report task according to the field name and the value corresponding to the field name and the preset rules includes:
according to the abbreviation rules, the field name is abbreviated to obtain the abbreviated field name;
and splicing the abbreviated field names according to the splicing rule to obtain the reporting task.
3. The method of claim 2, wherein a reporting link is preset, and the splicing the abbreviated field names according to the splicing rule to obtain the reporting task comprises:
and splicing the reporting link, the abbreviated field name and the value corresponding to the field name into the reporting task.
4. The method of claim 1, wherein the generated reporting task is added to a waiting queue, and is waiting for being added from the waiting queue to a reporting queue for reporting; reporting the reporting tasks in the reporting queue to a data statistics platform, comprising:
adding the generated reporting task into a waiting queue;
reporting the first reporting task in the reporting queue to a data statistics platform;
judging whether the first reporting task is reported successfully;
if so, deleting the first reporting task from the reporting queue, taking the next reporting task as the first reporting task, and acquiring the reporting task from the waiting queue and adding the reporting task to the reporting queue;
and if not, adding the first reporting task to the tail of the waiting queue, and deleting the first reporting task from the reporting queue.
5. The method of claim 4, wherein before adding the generated reporting task to the waiting queue, further comprising:
judging whether a reporting task exists in the reporting queue;
if so, adding the generated reporting task to the waiting queue for waiting to be reported;
and if not, adding the generated reporting task into the reporting queue to carry out reporting.
6. The method according to claim 4 or 5, wherein a database is preset, and the database is used for backing up all the non-reported reporting tasks in the reporting queue and the waiting queue, and the method further comprises:
before adding reporting tasks into the waiting queue, if the number of the reporting tasks in the waiting queue is equal to a preset number, deleting a first reporting task in the waiting queue from the waiting queue, wherein the preset number is the number of the reporting tasks when the waiting queue is full;
and when the number of the reported tasks in the waiting queue is less than the preset number, taking out the reported tasks which are not reported from the database and adding the reported tasks into the waiting queue.
7. The method according to claim 4 or 5, characterized in that the method further comprises:
in the process of reporting the reporting tasks in the reporting queue, acquiring performance parameters of the electronic equipment, wherein the performance parameters comprise refreshing frequency, memory occupancy rate and/or network speed;
and when the performance parameter is in a preset range, suspending the report of the report tasks in the report queue.
8. The method of claim 1, further comprising:
after the target data is obtained, if the execution of the application program corresponding to the target data is monitored to be finished, a step of generating a reporting task by the field name and the value corresponding to the field name according to a preset rule is executed.
9. A data collection device, for use with an electronic device, the device comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring target data collected based on embedded point information, and the target data comprises field names and values corresponding to the field names;
the generating module is used for generating the field name and the value corresponding to the field name into a reporting task according to a preset rule;
the adding module is used for adding the generated reporting task into a waiting queue and waiting for adding the generated reporting task from the waiting queue to a reporting queue for reporting;
and the reporting module reports the reporting tasks in the reporting queue to a data statistics platform.
10. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a memory electrically connected with the one or more processors;
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method of any of claims 1-8.
11. A computer-readable storage medium, having stored thereon program code that can be invoked by a processor to perform the method according to any one of claims 1 to 8.
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Application publication date: 20200121 Assignee: GUANGZHOU CUBESILI INFORMATION TECHNOLOGY Co.,Ltd. Assignor: GUANGZHOU HUADUO NETWORK TECHNOLOGY Co.,Ltd. Contract record no.: X2021440000030 Denomination of invention: Data collection method, device, electronic equipment and storage medium License type: Common License Record date: 20210125 |