WO2017101606A1 - 一种数据采集分析系统和方法 - Google Patents

一种数据采集分析系统和方法 Download PDF

Info

Publication number
WO2017101606A1
WO2017101606A1 PCT/CN2016/104923 CN2016104923W WO2017101606A1 WO 2017101606 A1 WO2017101606 A1 WO 2017101606A1 CN 2016104923 W CN2016104923 W CN 2016104923W WO 2017101606 A1 WO2017101606 A1 WO 2017101606A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
parameter
collection
application
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2016/104923
Other languages
English (en)
French (fr)
Inventor
王景正
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Qihoo Technology Co Ltd
Qizhi Software Beijing Co Ltd
Original Assignee
Beijing Qihoo Technology Co Ltd
Qizhi Software Beijing Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Qihoo Technology Co Ltd, Qizhi Software Beijing Co Ltd filed Critical Beijing Qihoo Technology Co Ltd
Publication of WO2017101606A1 publication Critical patent/WO2017101606A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/02Capturing of monitoring data
    • H04L43/022Capturing of monitoring data by sampling
    • H04L43/024Capturing of monitoring data by sampling by adaptive sampling
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/04Processing captured monitoring data, e.g. for logfile generation

Definitions

  • the present invention relates to the field of data processing technologies, and in particular, to a data acquisition and analysis method, a data acquisition and analysis system, a program, and a readable medium.
  • the smart terminal provides a variety of services by installing various applications to realize its functions.
  • developers of each service platform need to set up a data collection scheme to collect application data to understand business needs.
  • the application data collected by different services is different. Therefore, the developer of the service platform needs to set different application data collection schemes according to different services.
  • the developer of the service platform needs to set the collection parameters of each application according to the services provided by the service platform, collect data for each application according to the set collection parameters, and generate a service report of the service platform to understand the business requirements.
  • the developers of each service platform also need to define the data collection format of each application, so that each service platform can collect the data of each application according to the set data collection format, further increasing the workload of the developer.
  • the present invention has been made in order to provide a data acquisition and analysis method and a corresponding data acquisition and analysis system that overcome the above problems or at least partially solve the above problems.
  • a data collection and analysis system includes: an acquisition control server, a data analysis server, a report generation server, and at least one data terminal, wherein the data terminal is provided with an acquisition tool; the collection control server And configured to collect the configuration information to the data terminal and send the data to the corresponding data terminal, where the collection configuration information is used to control the collection of the collection parameters, and the data terminal is configured to invoke the collection tool when the application is running.
  • the data analysis server is configured to analyze the corresponding parameter information of each uploaded parameter and obtain the data And analyzing the result; sending the data analysis result to the report generation server; and the report generation server is configured to generate a data report according to the data analysis result.
  • the data collection and analysis method is provided to be applied to a data collection and analysis system
  • the data collection and analysis system includes: the collection control server, a data analysis server, a report generation server, and at least one data terminal.
  • An acquisition tool is installed in the data terminal; the method includes: the collection control server is configured to collect configuration information and send the configuration information to the data terminal, and the data terminal invokes the collection tool when the application is running. Collecting parameter information of the collected parameter according to the collected configuration information; the data terminal uploads the collected parameter information to the collection control server; the data analysis server analyzes the corresponding parameter information of each uploaded parameter, and obtains data analysis.
  • the data analysis server sends the data analysis result to the report generation server; the report generation server generates a data report according to the data analysis result.
  • a program comprising readable code, when the readable code is run on a computing device, causing the computing device to perform the method according to any of the embodiments of the present invention Data collection and analysis methods.
  • the embodiment of the invention further provides a readable medium, wherein the program according to the embodiment of the invention is stored.
  • the collection tool When the application starts and initializes, the collection tool is invoked.
  • the collection tool may collect parameter information of each collection parameter in the application according to the collection configuration information.
  • the collection tool determines whether the upload condition is met. If yes, the collection tool compresses the parameter information according to the preset algorithm, and then uploads the data to the data analysis server.
  • the data analysis server analyzes the corresponding parameter information of each uploaded parameter, such as the pair of each collection parameter.
  • the parameter information is collected to obtain the data analysis result, and the data analysis result is sent to the report generation server, and the report generation server configures the data analysis result of each logic according to the data analysis result.
  • the attribute information generates a data report so that the usage of the application can be determined based on the data report. Therefore, the collection tool can collect the parameter information of each collection parameter in the data terminal of the application operation, and after uploading to the data analysis server, perform data analysis according to the statistical requirement, thereby generating a data report of the corresponding service, and obtaining the user requirement through the data report. , habits, etc., to adjust the business, more in line with user needs.
  • FIG. 1 is a block diagram showing the structure of a data acquisition and analysis system according to an embodiment of the present invention
  • FIG. 2 is a flow chart showing the steps of a data acquisition and analysis method according to an embodiment of the present invention
  • FIG. 3 is a block diagram showing the structure of a data acquisition and analysis system according to another embodiment of the present invention.
  • FIG. 4 is a flow chart showing the steps of a data acquisition and analysis method according to another embodiment of the present invention.
  • FIG. 5 is a flow chart showing the steps of a custom event processing method according to another embodiment of the present invention.
  • FIG. 6 is a flow chart showing the steps of a test method of a target application according to another embodiment of the present invention.
  • FIG. 7 is a flow chart showing the steps of a transmission verification method according to another embodiment of the present invention.
  • FIG. 8 is a flow chart showing the steps of a data quality verification method according to another embodiment of the present invention.
  • Figure 9 shows a block diagram of a computing device for performing a data acquisition analysis method in accordance with the present invention.
  • Figure 10 illustrates a memory unit for holding or carrying program code implementing a data acquisition analysis method in accordance with the present invention.
  • Embodiments of the present invention provide a data collection and analysis system, which is versatile and can collect, analyze, and generate different service reports for various applications.
  • FIG. 1 a block diagram of a data acquisition and analysis system in accordance with one embodiment of the present invention is shown.
  • the data collection and analysis system includes: an acquisition control server 102, a data analysis server 104, a report generation server 106, and at least one data terminal 108, in which an acquisition tool is installed.
  • the collection control server 102 is configured to configure the collection configuration information to the data terminal and send the data to the corresponding data terminal, where the collection configuration information is used to control the collection of the collection parameters, and the data terminal 108 is used in the application.
  • the collection tool is invoked during operation, and the parameter information of the collection parameter is collected according to the collection configuration information; and the collected parameter information is uploaded to the data analysis server; the data analysis server 104 is configured to upload the collected parameters.
  • the data analysis result is obtained, and the data analysis result is sent to the report generation server.
  • the report generation server 106 is configured to generate a data report according to the data analysis result.
  • FIG. 2 there is shown a flow chart of the steps of a data acquisition analysis method in accordance with one embodiment of the present invention.
  • Step 202 The collection control server configures the collection configuration information to the data terminal and sends the configuration information to the corresponding data terminal.
  • Step 204 The data terminal invokes the collection tool when the application is running, and collects parameter information of the collected parameter according to the collected configuration information.
  • Step 206 The data terminal uploads the collected parameter information to the collection control server.
  • Step 208 The data analysis server analyzes the uploaded parameter information of each collected parameter, and obtains a data analysis result.
  • Step 210 The data analysis server sends the data analysis result to the report generation server.
  • Step 212 The report generation server generates a data report according to the data analysis result.
  • the application of the embodiment of the present invention refers to an application installed on the terminal, such as a mobile phone assistant, a browser, a security guard, a player, and the like.
  • Collection tools include the Software Development Kit (SDK).
  • SDK Software Development Kit
  • the collection control server can configure the collection parameters of each application and collect configuration information to generate control information of the collection tool.
  • the collection tool may collect parameter information of each collection parameter in the application according to the collection configuration information.
  • the collection configuration information is used to control collection and upload of the collection parameters.
  • the acquisition parameters include static parameters and/or dynamic parameters.
  • the static parameter may be used to collect static parameter information corresponding to the application; the dynamic parameter may be used to collect dynamic parameter information when the application is running.
  • the collection tool is invoked.
  • the collection tool may collect parameter information of each collection parameter in the application according to the collection configuration information.
  • the collection tool determines whether the upload condition is met. If yes, the collection tool compresses the parameter information according to the preset algorithm, and then uploads the data to the data analysis server.
  • the data analysis server analyzes the parameter information corresponding to each of the uploaded collection parameters, such as performing statistics on the parameter information corresponding to each collection parameter, thereby obtaining the data analysis result, and then sending the data analysis result to the report generation server,
  • the report generation server generates a data report by configuring readable attribute information for each logical data analysis result according to the data analysis result, so that the application usage can be determined based on the data report. Therefore, the collection tool can collect the parameter information of each collection parameter in the data terminal of the application operation, and after uploading to the data analysis server, perform data analysis according to the statistical requirement, thereby generating a data report of the corresponding service, and obtaining the user requirement through the data report. , habits, etc., to adjust the business, more in line with user needs.
  • the collection control server 102 includes a cloud control server 1022.
  • the cloud control server 1022 is configured to determine an acquisition parameter of the application according to an application type, where the collection parameter includes: a dynamic parameter and/or a static parameter;
  • the terminal is configured to collect configuration information, where the collection configuration information is used to control the collection and uploading of the collection parameters, and the collection parameters and the collection configuration information are sent to the data terminal where the application is located.
  • the cloud control server 1022 is configured to configure an upload condition and/or a sampling condition of the parameter information, and add an upload condition and/or a sampling condition to the collection configuration information; and configure a collection threshold corresponding to the memory of the terminal where the application is located, The collection threshold is added to the collection configuration information; the uploading interval corresponding to the network type of the terminal where the application is located is configured, and the uploading interval is added to the collection configuration information; and the cache threshold of the terminal where the application is located is configured, The cache threshold is added to the acquisition configuration information; and the priority of the protocol upload sequence, the sampling rate, and the sampling parameter are configured in the collection configuration information.
  • the data terminal 108 is configured to collect the parameter information of the static parameter of the application according to the collection configuration information by using the collection tool, and determine the dynamic parameter to be collected according to the collection configuration information by using the collection tool, according to the operation of the application.
  • the parameter information of the dynamic parameter is collected in real time.
  • the data terminal 108 is configured to: when the interface switching of the application is detected, record the interface before the switching as the previous page, record the switched interface as the current page, and add the previous page and the current page to the application.
  • the interface startup information when the button of the application is detected, the button number corresponding to the button is acquired, the number of clicks corresponding to the button number is updated, and the button number and the click number are added to the button click information. Collecting the running time related to the application as duration information, wherein the duration information Including: interface runtime and application runtime.
  • the application can be used to collect and upload the parameter information in the data terminal to generate a corresponding report.
  • the specific steps are as follows:
  • FIG. 4 there is shown a flow chart of the steps of a data acquisition and analysis method in accordance with another embodiment of the present invention.
  • Step 402 The collection control server determines an acquisition parameter of the application according to an application type.
  • the cloud server can configure acquisition parameters of each application and collect configuration information to generate control information of the collection tool.
  • the cloud server can control the data collection of each application by the terminal where the application is located by using the control information of the collection tool.
  • the collection parameters include: dynamic parameters and/or static parameters.
  • the parameter information of the static parameter includes at least one of the following: a terminal identifier, a version information, a channel information, a network type, and resolution information.
  • the parameter information of the dynamic parameter includes at least one of the following: an application interface startup information, and a button click information.
  • the static parameter can be used to collect the static parameter information corresponding to the application, such as the identification information, version information, channel information, network type, and resolution information of the terminal where the application is located.
  • the identifier information of the terminal may be used to identify the terminal where the application is located. For example, the M2 value may be calculated based on information such as the hardware of the terminal.
  • the M2 value may be calculated by using a serial number, a model, a version information, etc., and the M2 value can identify different
  • the terminal does not disclose the hardware information of the terminal to ensure the privacy of the user; the version information can be used to record the version corresponding to the application, such as the operating system version of the terminal, the software version or the software development kit version, etc.; the channel information can be used.
  • the network device is used to determine the network type of the terminal where the application is connected; the resolution information is used to determine the display resolution of the terminal where the application is located, and the display resolution may be referred to as a screen resolution.
  • the dynamic parameter can be used to collect parameter information generated by the application during the running process, such as application interface startup information, button click information, duration information, abnormal information, and session information.
  • the application interface startup information is used to record the page before the switching of the interface of the application and the interface after the switching;
  • the button click information is used to record the button number corresponding to each button in the application and the number of clicks corresponding to the button number;
  • the duration information is determined according to the startup time point and the shutdown time point, such as the application running time and the interface running time;
  • the abnormal information is used to record the information of the application running abnormality, such as the time point or the number of times the application fails to start;
  • the session information is used to record the application.
  • the message of the session class generated at runtime.
  • Step 404 The collection control server collects configuration information according to the configuration of the application and the terminal where the application is located.
  • the step of collecting configuration information according to the application and the terminal where the application is configured includes at least one of the following: an upload condition and/or a sampling condition of the configuration parameter information, and an upload condition and/or a sampling condition are added to the collection configuration information;
  • the upload interval of the network type corresponding to the terminal where the application is located is added, and the upload interval is added to the collection configuration information;
  • the terminal where the application is located corresponds to a cache threshold, and the cache threshold is added to the collection configuration information.
  • the priority of the protocol upload sequence, the sampling rate, and the sampling parameter are configured in the collection configuration information.
  • Step 406 The collection control server sends the collection parameters and the collection configuration information to the data terminal where the application is located.
  • the collection configuration information is used to control collection and upload of the collection parameters.
  • the application and the terminal where the application is located are collected according to the collection configuration information, and the collected data needs to be uploaded according to the collection configuration information. Therefore, the cloud server can set the collection configuration information according to the application to be collected and the terminal where the application is located, so that the terminal of each application or application can collect and upload the collection parameters according to the collection configuration information.
  • the uploading condition is used to control uploading of the parameter information according to the uploading success flag bit
  • the sampling condition is used to control the collection of the parameter information according to the test identifier.
  • the cloud server can set the sampling condition and add the sampling condition to the collection configuration information, so that the terminal where the application is located collects data according to the sampling condition in the collection configuration information. Specifically, by detecting, it can be determined whether the data of the application meets the sampling condition. For example, when the application has the test identifier, all the parameter information of the application meets the sampling condition, and the collection tool acquires the parameter information of each static parameter and the parameter information of the dynamic parameter in the application. For example, in the process of maintaining the application, the developer constantly updates the version of the application according to the requirements, and some of the versions are beta versions of the beta version. After the test is passed, the official version will be launched, and the test logo can be configured for the beta version of the application.
  • the collected parameter information can also be cached locally.
  • the parameter information satisfies the upload condition in the sampling configuration information
  • the parameter information is uploaded.
  • the cloud server may set an uploading condition of each parameter information by setting a priority or an uploading interval of each parameter information, and save the uploading condition to the collecting configuration information.
  • the terminal where the application is located may compress the parameter information and upload it to the cloud server, that is, upload the parameter information that satisfies the uploading condition.
  • the cloud server can set upload conditions for different parameter information, and add to the collection configuration information, and then the uploading of each parameter information can be controlled by the upload condition.
  • the collection threshold of the memory corresponding to the terminal where the application is located is added, and the collection threshold is added to the collection configuration information.
  • the collection threshold is used to determine the collected acquisition parameters according to the memory information of the terminal.
  • some terminals have a large memory such as 2G in memory, and some terminals have small memory. In order to reduce the impact of data collection on the terminal, the terminal can run the application normally.
  • the server can collect the threshold according to the memory setting of the terminal where the application is located, and add the collection threshold to the collection configuration information, so that the collected collection parameters can be controlled according to the memory information of the terminal. For example, if the collection threshold is 50M, the memory of the terminal can be limited to 50M. You can limit the collection of the collection parameters without affecting the usage of the terminal. If no dynamic parameters are collected, only static parameters such as the terminal identifier can be uploaded once. As a specific example of the present invention, when the memory information of the terminal where the application is located does not reach the collection threshold, the parameter information corresponding to the dynamic parameter of the application on the terminal may not be collected, and the parameter information corresponding to the static parameter may be collected, such as the collection terminal.
  • the parameter information of each collection parameter in the application is collected according to the collection configuration information, such as the parameter information of the static parameter and the parameter information of the dynamic parameter in the application.
  • the uploading interval of the network type corresponding to the terminal where the application is located is configured, and the uploading interval is added to the collection configuration information.
  • the uploading interval is an interval of timing uploading, such as 5 minutes, 10 minutes, and the like. In essence, data is transmitted at different rates through different types of networks. Therefore, the upload interval of the network type corresponding to the terminal where the application is located can be set according to the data transmission rate corresponding to the network type, and the upload interval of different network types is added to the collection configuration information.
  • the uploading interval corresponding to the network type may be selected according to the type of the network to which the terminal is located, so that each application can upload the parameter information of the collected parameter according to the data transmission rate of the currently connected network, so that the application can be fully utilized. Network resources, and guarantee the upload rate of parameter information.
  • the upload interval may be determined according to the network type and the priority of the collection parameter itself.
  • the cache threshold of the terminal where the application is located is configured, and the cache threshold is added to the collection configuration information. The cache threshold is used to determine the amount of data of the cached parameter information at the terminal. Specifically, the performance of different terminals is different, so the amount of data of parameter information that can be cached is different.
  • the cache threshold corresponding to the terminal can be set according to the amount of data that can be cached by the terminal, and the cache threshold is added to the collection configuration information.
  • the cloud server may control the terminal to delete the parameter information of the cache time before the cached parameter information does not exceed the cache threshold, thereby ensuring the efficiency of data collection. For example, if the cache threshold is set to 2M, and the local cache is determined to exceed 2M when the collection parameter information is to be stored, the parameter information may be deleted from the front in the order of time before the storage parameter is stored, and the storage parameter does not exceed 2M.
  • the priority of the protocol upload order, the sampling rate, and the sampling parameters are configured in the collection configuration information.
  • the protocol uploading sequence is used to determine an uploading protocol of the collecting parameter, where the sampling rate is used to determine the sampled terminal, and the priority is used to determine the number of times the parameter information is collected and the uploading interval.
  • the cloud server may perform statistics on the network transmission protocol used by the network, determine the priority of each network transmission protocol, and generate a protocol uploading sequence.
  • the protocol uploading sequence may be as follows: 1. Transmission Control Protocol (TCP); 2. Wireless Application Protocol (WAP); 3. User Datagram Protocol (UDP); Real-time Transport Protocol (RTP); 5. Hypertext Transfer Protocol (HTTP).
  • TCP Transmission Control Protocol
  • WAP Wireless Application Protocol
  • UDP User Datagram Protocol
  • RTP Real-time Transport Protocol
  • HTTP Hypertext Transfer Protocol
  • the sequence number corresponding to the network transmission protocol may represent the priority of the network transmission protocol.
  • the protocol uploading sequence of the above example the parameter information is preferably uploaded using the highest priority TCP protocol.
  • the WAP protocol is used for uploading, that is, the uploading protocol is selected according to the priority order, so as to avoid the problem that the parameter information upload fails due to the terminal and the application not supporting the use of a certain network transmission protocol, and the uploading efficiency and uploading of the parameter information are guaranteed. quality.
  • the cloud server can perform statistics on the terminal where the application is located to determine the sampling rate.
  • the sampling rate the number of terminals to be sampled can be determined, and the terminal where the application is located can be randomly selected according to the determined number of terminals, and the selected terminal is used as the target terminal, and the terminal determined as the sampling.
  • the terminal identifier of each terminal may be calculated by a preset algorithm, and the target terminal is selected, for example, the target terminal is determined by the last digit or two digits of the terminal identifier.
  • the cloud server may determine the sampled terminal by using other methods, for example, by performing modulo or suffixing on the terminal identifier to determine the sampled terminal, which is not limited in this embodiment of the present invention.
  • the cloud server can control the number of terminals to be sampled, avoiding the problem of large data processing pressure of the cloud server by sampling a large number of terminals, ensuring the sampling efficiency of the data, and thereby accelerating the progress of data collection.
  • the cloud server can also control the collection times and upload intervals of the parameter information of the collection parameters by setting the priority of each collection parameter.
  • the information of the collection parameter may be collected according to the collection times corresponding to the determined priority, and uploaded according to the upload interval corresponding to the priority.
  • the parameter information of the collection parameter such as the priority of the acquisition parameter I is A level
  • the collection number of the parameter information of the collection parameter I is 1000 times
  • the upload interval is 20 minutes, that is, every 20 minutes, the uploading is performed once every 20 minutes.
  • the parameter information of parameter I is collected.
  • Priority of acquisition parameters Number of times the parameter information is collected Parameter information upload interval Class A 1000 times 20 minutes Class B 700 times 1 hour Class C 300 times 3 hours Class D 10 times 12 hours Class F 1 time 24 hours
  • the priority of the collection parameter and the number of times of the parameter information collection and the upload interval corresponding to each priority may be set in advance according to the service requirement or the characteristics of the collected data, so that the cloud server can pass the priority of the collection parameter.
  • Step 408 Collect the parameter information of the static parameter of the application according to the collection configuration information by using the collection tool.
  • Step 410 The collection tool determines the dynamic parameter to be collected according to the collection configuration information, and collects the parameter information of the dynamic parameter in real time according to the running of the application.
  • the collection parameters may be collected during the application running, including: determining the number of times the parameter information of the collection parameter is collected according to the priority of each collection parameter in the configuration information. And upload interval. Acquiring the memory information of the mobile terminal where the application is located, and determining whether the memory information reaches the collection threshold; when the memory information does not reach the collection threshold, collecting the collection parameters of the static parameter and uploading the parameters to the server to end the collection step
  • the application runtime invokes the collection tool to collect parameter information of each acquisition parameter in the application, where the collection parameter includes a static parameter and/or a dynamic parameter.
  • some terminals have a large memory such as 2G in memory, and some terminals have small memory.
  • the terminal can run the application normally.
  • the server can collect the threshold according to the memory setting of the terminal where the application is located, and add the collection threshold to the collection configuration information, so that the collected collection parameters can be controlled according to the memory information of the terminal.
  • the memory information of the terminal where the application is located does not reach the collection threshold. If the value of the terminal is less than 50M, the value of the parameter corresponding to the static parameter may be collected, such as the identifier of the collection terminal.
  • the collection of the collection parameters can be limited. If the dynamic parameters are not collected, only the static parameters such as the terminal identifier can be uploaded once.
  • the step of collecting parameter information of the dynamic parameter in real time according to the running of the application includes at least one of the following:
  • the interface before the record switching is the previous page
  • the interface after the record switching is the current page
  • the previous page and the current page are added to the application interface startup information. That is, when the user accesses the record in the application interface, in order to ensure the continuity of the access, the previous access interface may be recorded while recording the current interface, so that each interface record is the current page + the previous page, of course, if it is the home page, The previous page is empty.
  • the application can include a number of buttons, each button can be numbered to identify a different button, so that when the button is clicked, the button number and the number of clicks are recorded, that is, the number of clicks is initially 0, and each click is incremented by one.
  • the application can be run in a multi-process mode.
  • the application starts with the main process record start time point, and the last process records the end time point.
  • the main process may not be fully started.
  • the running time of the record may be negative, or the time between the start time of the last start and the end time of the current close will be calculated, and the length of time will be too long, resulting in a record of the duration. accurate.
  • the running time related to the application is collected as the duration information, where the duration information includes: an interface running time and an application running time.
  • the collecting the running time related to the application as the duration information includes: the main process of the application records a start time point and an end time point, and the running time is recorded according to the start time point and the end time point, and the running is performed. Time is used as duration information. That is, in the embodiment, for the application running in multiple processes, the records of the start and end times are recorded from the main process, that is, the start time point of the main process record is used when the application starts, and the application time is closed by the end time of the main process record. The difference between the end time point and the start time point is the running time, ensuring accurate recording of the running time.
  • the collected parameter information may be cached locally.
  • a cache threshold may be configured, where the cache threshold is used to determine parameter information cached in the terminal.
  • the amount of data Specifically, the performance of different terminals is different, so the amount of data of parameter information that can be cached is different.
  • the cache threshold corresponding to the terminal can be set according to the amount of data that can be cached by the terminal, and the cache threshold is added to the collection configuration information.
  • the cloud server may control the terminal to delete the parameter information of the cache time before the cached parameter information does not exceed the cache threshold, thereby ensuring the efficiency of data collection.
  • the cache threshold is set to 2M
  • the local cache is determined to exceed 2M when the collection parameter information is to be stored
  • the parameter information may be deleted from the front in the order of time before the storage parameter is stored, and the storage parameter does not exceed 2M.
  • Step 412 The data terminal uploads the collected parameter information to the collection control server.
  • the upload interval processing is determined according to the parameter priority.
  • the upload interval can be determined according to the current network type to determine whether the current time meets the upload interval.
  • you can also configure the upload threshold that is, the threshold for each data upload, and check whether the current cached parameter information is greater than the upload threshold.
  • the cloud server may set an uploading condition of each parameter information by setting a priority or an uploading interval of each parameter information, and save the uploading condition to the collecting configuration information.
  • the embodiment of the present invention uploads parameter information to the server through data packet uploading. If a packet contains too much data, it is easy to cause the upload to fail.
  • the size of each upload data packet is limited by uploading a threshold.
  • the packetization measure is adopted, that is, the parameter information is divided into at least two data packets. Subcontract uploading can avoid upload failures caused by excessive data volume. For example, when the upload threshold is 100k, when the parameter information to be uploaded is greater than 100k, the parameter information can be divided into at least two.
  • the data packet for example, the parameter information to be uploaded is 250k, and can be divided into three data packets 100k, 100k and 50k. Then, the parameter information is compression-encoded according to a preset algorithm to generate a parameter data packet.
  • the uploading protocol is selected according to the uploading sequence of the preset protocol, and the parameter information is uploaded to the server according to the uploading protocol.
  • uploading failures may occur when parameter information is uploaded to the server. In this case, you may need to upload the parameter information that has not been uploaded. In order to distinguish the uploading of the parameter information, you can configure the upload success flag according to the upload result.
  • the upload result is identified by uploading a success flag bit.
  • the upload success flag is successfully set.
  • the mobile terminal where the application is located is unlocked, the upload success flag is detected.
  • the upload success flag is detected.
  • the upload success is marked as failed, the current network type is obtained, and it is determined whether the network type allows uploading data.
  • the current network type can be obtained, and whether the network type is allowed to upload data, such as whether the network is connected or not, is determined to be 2G, 3G, 4G or WIFI and so on. If yes, that is, when the network type allows uploading data, the parameter information that is not uploaded is uploaded to the server.
  • the upload success flag bit is detected, and the uploading of the parameter information is determined. If the upload success is marked as failed, the current network type is obtained, and it is determined whether the network type is allowed to upload data.
  • the step of uploading the unuploaded parameter information to the server is performed.
  • Step 414 The data analysis server analyzes the uploaded parameter information of each collected parameter, and obtains a data analysis result.
  • Step 416 The data analysis server sends the data analysis result to the report generation server.
  • Step 418 The report generation server generates a data report according to the data analysis result.
  • the data analysis server analyzes the parameter information corresponding to each of the uploaded collection parameters, such as performing statistics on the parameter information corresponding to each collection parameter, thereby obtaining the data analysis result, and then sending the data analysis result to the report generation server,
  • the report generation server generates a data report by configuring readable attribute information for each logical data analysis result according to the data analysis result, so that the application usage can be determined based on the data report.
  • the collection tool is called when the application is running; the collection tool collects the parameter information of each collection parameter in the application; determines the upload interval according to the current network type, determines whether the current time meets the upload interval; and when the current time reaches the upload interval, And compressing the parameter information according to a preset algorithm to generate a parameter data packet; uploading the parameter data packet to a server, so that the server performs data analysis according to the parameter information.
  • the report generation server 106 is configured to obtain service statistics information according to the customized management information of the configured application corresponding to the customized event, and generate a customized event report according to the customized management information and the service statistics.
  • statistics are collected on events, it is often only possible to perform statistics on common events.
  • General events can only be used for statistics on common features, while for some unique features, general events are used for statistics, and the statistical effect is not obvious.
  • each application on the terminal is customized according to the service that needs statistics, and a custom event is generated, and the customized management information is configured according to the custom event corresponding to each application. .
  • the report generation server 106 is further configured to: obtain an application path of the application from the service management page, and the customized event information of the application corresponding to the customized event, where the customized event information includes: an event Name and event attributes; use the application path and custom event information to generate custom management information.
  • the report generation server 106 is configured to determine an application according to the application path, and obtain, for each custom event, a logical name corresponding to the event name, and a logical attribute corresponding to the event attribute; Collecting parameters, determining service statistics information corresponding to the collection parameters according to the logical attributes; determining an event name corresponding to each collection parameter, and generating a customized event report of the application by using the event name and the service statistics information of the corresponding collection parameter.
  • the report generation server generates a data report according to the data analysis result, and the report generation server obtains service statistics information according to the customized management information of the configured application corresponding to the customized application; and according to the customized management information and service Statistics generate custom event reports.
  • the step of configuring the custom management information the application path of the application is obtained from the service management page, and the custom event information corresponding to the custom event is used by the application, where
  • the customized event information includes: an event name and an event attribute; and the customized management information is generated by using the application path and the customized event information.
  • the service statistics information is obtained, and the customized event report is generated according to the customized management information and the service statistics, including: determining an application according to the application path; Defining an event, obtaining a logical name corresponding to the event name, and a logical attribute corresponding to the event attribute; searching for the logical name corresponding to the collection parameter, determining, according to the logical attribute, service statistics information corresponding to the collection parameter; determining each Collect the event name corresponding to the parameter, and generate the application's custom event report by using the event name and the service statistics of the corresponding collection parameter.
  • FIG. 5 a flow chart of the steps of a custom event processing method in accordance with another embodiment of the present invention is shown.
  • Step 502 Feedback the service management page according to the configuration request.
  • Step 504 Obtain an application path of the application from the service management page, and apply custom event information corresponding to the customized event.
  • Step 506 Generate custom management information by using an application path and custom event information. Customize some unique events applied in the mobile terminal to enable statistics on some unique data in the application through custom events.
  • the corresponding custom event of the application is processed and fed back to the service management page, and the application path corresponding to the application is obtained from the service management page, for example, according to each custom event, which service belongs to it, and then according to Determining the service information, determining the application corresponding to the service, determining the application path corresponding to the application, and obtaining the customized event information corresponding to the custom event, wherein the customized event information includes: an event name and an event attribute,
  • the defined event includes at least one of the following: a traffic statistics event, a click event, and a selected event.
  • Event attributes include: how statistics are customized for events. Generate custom management information for application paths, event names for custom events, and event properties. For example, the statistics of the traffic consumption in a certain period of time, the traffic statistics event is set as a custom event; and the traffic of all the applications in the period is consumed; the corresponding application path of the application is obtained, and the time is found. Only the mobile assistant and the browser consume traffic, and the mobile assistant and the browser consume traffic during this period of time as custom management information.
  • Step 508 determining an application according to the application path.
  • Step 510 Acquire, for the application, the service statistics information corresponding to the event name and the event attribute of the respective defined event.
  • the application is determined according to the application path in the service management page, and the service statistics corresponding to the event name and the event attribute of each custom event are obtained from the application after the application path is determined.
  • the cloud server can send the collection parameters and collection configuration information to the terminal where the application resides.
  • the collection tool can call the SDK (Software Development Kit) to collect data for each application, that is, collect the collection parameters in the application according to the collection configuration information.
  • Parameter information wherein the acquisition parameters include static parameters and dynamic parameters.
  • the service statistics can be performed.
  • the obtaining the service statistics information according to the customized management information includes the following sub-steps: obtaining, for each custom event, a logical name corresponding to the event name, and a logical attribute corresponding to the event attribute. Find the logical parameter corresponding to the collection parameter, and determine the service statistics corresponding to the collection parameter according to the logical attribute.
  • the server performs data processing and data statistics according to the customized management information.
  • each custom event there is a corresponding event name and a corresponding logical name.
  • a button in the page triggers an event, and the middle button of the page is in turn
  • the number is specified, and the button trigger event is defined as a button event.
  • the event name is button 1
  • the corresponding logical name is button.
  • Each custom event has a logical attribute, and statistics are used to count each custom event.
  • a page button trigger event is defined as button event 1, which is triggered once, accumulated, and its final value is obtained. . According to each custom event, obtain the logical name corresponding to each custom event name, and the logical attribute corresponding to the event attribute.
  • the so-called logical name and logical attribute are actually a representation of the custom event in the underlying code, the background server
  • the data is counted by logical name and logical attribute.
  • Each application corresponds to a service, and each service has multiple custom events, and the collection parameters corresponding to the custom event are searched according to the logical name of each event, according to the logic.
  • the attribute is collected and the statistics of the collected parameters are statistically obtained, and the service statistics corresponding to the customized event are obtained.
  • the service statistics corresponding to each custom event are determined. For example, if a page includes three paragraphs of text, it is necessary to count the number of times each of them is selected and copied; define it as a service, and then define three custom events, such as the first paragraph is selected and copied.
  • the event is defined as selected, the second segment is selected and the copied event is defined as selected 2, the third segment is selected and the copied event is defined as selected 3; the logical name selected by the custom event is check; the collection parameters include Defines the number of executions selected by the event, that is, the number of times each piece of text is selected and copied. For example, in a certain period of time, the first paragraph of text is selected and the number of times of copying is 0, the second paragraph of text is selected and the number of times of copying is 1, the third paragraph of text is selected and the number of times of copying is 6.
  • the event name is selected, the logical name is check1, and the service statistics corresponding to the collection parameter are 0; the event name is selected 2, the logical name is check2, the service statistics corresponding to the collection parameter is 1; and the event name is selected.
  • the logical name is check3, and the service statistics corresponding to the collection parameters are 6. Determine the logical name corresponding to the event name according to the event name, determine the logical attribute corresponding to the event attribute according to the event attribute, and then determine the corresponding collection parameter and service statistics information according to the logical name and the logical attribute; the service corresponding to each custom event can be clearly determined. Statistics.
  • Step 512 Determine an event name corresponding to each collection parameter, and generate a customized event report of the application by using the event name and the service statistics information of the corresponding collection parameter.
  • the data analysis server receives the parameter information, and determines the event name, the logical name, and the service statistics corresponding to the collection parameter corresponding to the custom event according to the parameter information; and the service corresponding to the event name, the logical name, and the collection parameter of the custom event.
  • the statistics information is sent to the report generation server; the report generation server determines a plurality of custom events corresponding to the service according to each service, and then determines, according to the defined event, an event name, a logical name, and an acquisition parameter corresponding to the custom event.
  • the service statistics information is generated according to the event name corresponding to each custom event and the service statistics corresponding to the collection parameter, where the service statistics information is the collection data corresponding to the collection parameters, and the collected data is accumulated in an accumulated manner. statistics.
  • Step 514 Obtain service statistics information corresponding to the general event information, and add the general event corresponding service statistics information to the custom event report.
  • An optional embodiment of the present invention only needs to obtain the corresponding service statistics information according to the event name corresponding to the common event for the general event, and add the event name of the common event and the service statistics corresponding to the common event to the custom event.
  • the embodiment of the present invention obtains the application path of the application from the service management interface, and applies the customized event information corresponding to the customized event; determines the application according to the application path, and obtains the service corresponding to the event name and the event attribute of the respective defined event for the application.
  • the statistics information is generated according to the service statistics information.
  • Each application corresponds to a service.
  • a service includes multiple custom events.
  • the custom event report is generated according to the service statistics corresponding to each custom event.
  • the service statistics corresponding to each custom event can be displayed in an intuitive manner.
  • the statistical method is more representative, and some unique events can be counted, and the statistical effect is enhanced.
  • the event is added to the custom event report, and the combined statistics of the common event and the custom event are implemented, so that the user can obtain the statistics of various events required from a business report to meet various user requirements.
  • the collection control server is further configured to configure test information corresponding to the test device of the target application; the data analysis server is further configured to analyze parameter information corresponding to the uploaded target application; and determine the parameter information.
  • the collection control server 102 includes: a development configuration server 1024.
  • the development configuration server is configured to: after the target application completes registration, configure a test identifier of the at least one test device for the target application; Configuring the collection parameter to be tested, and using the test identifier and the collection parameter as test information; the data analysis server is further configured to obtain parameter information of the target application corresponding collection parameter from the uploaded parameter information; The terminal parameter corresponds to the terminal identifier; determining whether the terminal identifier is the same as the test identifier in the test device table. When the terminal identifier is the same as any one of the test identifiers in the test device table, determining that the parameter information belongs to the test device.
  • the method further includes: the collection control server configuring test information corresponding to the test device of the target application; the data analysis server analyzing parameter information corresponding to the uploaded target application; determining that the parameter information belongs to the test device Real-time participation in the test equipment The number information is analyzed; when the report generation server determines that the parameter information belongs to the test device, the data report is generated in real time according to the data analysis result.
  • Configuring the test information of the test device corresponding to the target application including: after the target application is registered, configuring a test identifier of the at least one test device for the target application; configuring the collection parameter to be tested for the target application, The test identifier and the collection parameter are used as the test information.
  • the method further includes: the data analysis server obtains parameter information of the target application corresponding to the collection parameter from the uploaded parameter information; and the terminal parameter corresponding to the terminal identifier in the parameter information; Whether the terminal identifier is the same as the test identifier in the test device table. When the terminal identifier is the same as any test identifier in the test device table, the parameter information is determined to belong to the test device.
  • the steps for configuring the target application and testing the configuration server 1024 are as follows:
  • FIG. 6 a flow chart of the steps of a test method for a target application in accordance with another embodiment of the present invention is shown.
  • Step 602 Receive a registration request of the target application.
  • Step 604 Assign an application identifier to the target application according to the registration request.
  • the corresponding collection parameters can be collected during the application running process to determine the running status of the application.
  • each application uses a common collection tool, so it is possible to pre-test the application calling collection tool for parameter collection.
  • the application that needs to be tested can be targeted.
  • the test of the target application usually needs to know the test result in real time, so the test device can be configured for the target application, and the collection result of the test device can be analyzed in real time.
  • the target application is registered, and a registration request may be sent.
  • the registration request carries relevant information of the target application, and the server obtains an application identifier according to the registration request for the target application, so that an application is uniquely identified by the application identifier.
  • the collection tool that is, the SDK required to collect the data, can be sent to the target application, so that the target application can call the collection tool to collect at runtime.
  • Step 606 Configure a test identifier of the at least one test device for the target application.
  • Step 608 Configure the collection parameters to be tested for the target application, and use the test identifier and the collection parameters as test information.
  • the terminal identifier of the test device such as the M2 value
  • the development configuration server configures the terminal identifier as the test identifier of the test device, so that the test identifier of at least one test device can be configured for the target application.
  • the acquisition parameters to be tested by the target application that is, to determine the acquisition parameters that need to be collected from the target application during the test, thereby obtaining the parameter information of the corresponding acquisition parameters. Test identification and acquisition parameters are used as test information.
  • the target application can call the collection tool to collect, that is, the target application is a test application that adds the collection tool.
  • the cloud server generates the collection configuration information according to the collection parameters and the corresponding collection policy, and sends the collection configuration information to each data terminal, so that each corresponding application can report the parameter information corresponding to the collection parameter according to the collection configuration information, that is, the cloud server can
  • the terminal where the application is located collects the parameter information corresponding to each collection parameter by collecting parameters and collecting configuration information, and automatically completes the application data collection.
  • the terminal device invokes the collection tool according to the collection configuration information, such as calling the SDK to collect parameters of the target application, and uploading the collected parameter information to the data analysis server.
  • Step 610 Obtain parameter information of the target application corresponding collection parameter from the uploaded parameter information.
  • Step 612 Analyze the source of the parameter information to determine whether the parameter information belongs to the test device.
  • the data analysis server obtains the parameter information of the corresponding acquisition parameter of the target application from the uploaded parameter information, and then searches for the terminal identifier corresponding to the terminal parameter from the parameter information, and compares the terminal identifier with the test identifier in the pre-configured test device table to determine Whether the terminal identifier is the same as the test identifier in the test device table.
  • the parameter information is determined to belong to the test device, that is, the parameter information is collected from the test device. .
  • determining whether the parameter information belongs to the test device may include: determining, by using the terminal identifier corresponding to the terminal parameter in the parameter information, the source of the parameter information; determining whether the terminal identifier is the same as the test identifier in the test device table.
  • the judgment parameter information belongs to the test device.
  • the test identifier of each test device may be saved in the server, and a corresponding test device table is generated to facilitate determining the test device during subsequent analysis. The terminal identifier corresponding to the terminal parameter is searched from the parameter information, and the terminal identifier can identify the source of the parameter information, that is, which terminal is collected.
  • the terminal identifier Compare the terminal identifier with the test identifier in the test equipment table. It is determined whether the terminal identifier is the same as the test identifier in the test device table, that is, whether the current parameter information belongs to the test device. If the terminal identifier is the same as any one of the test identifiers in the test device table, the parameter information is determined to belong to the test device, that is, the parameter information is collected from the test device. On the other hand, if the terminal identifier is different from the test identifier in the test device table, the parameter information is not collected from the test device, that is, the parameter information does not belong to the test device, and the report can be generated according to the general processing flow, without errors. Real-time statistics.
  • the terminal identifier is used to determine whether the uploaded parameter information is from the test device. If yes, the parameter information belongs to the test device, and step 614 is performed; if not, the parameter information does not belong to the test device, and the process is ended without real-time statistics.
  • Step 614 Perform statistics on the corresponding parameter information according to a statistical manner for each parameter information belonging to the test device.
  • Step 616 Generate a test report according to the statistical result corresponding to each parameter information. After determining that the parameter information belongs to the test device, the parameter information of the test device is processed, and the corresponding parameter information is statistically calculated according to a statistical manner. If the number of times a button is triggered on a page, all the buttons on the page are numbered, that is, each button has its own corresponding number. The button is triggered once, and the number of times the button is triggered is superimposed. For example, the button numbered 1 triggers. 3 times, that is, the corresponding statistics data includes button 1 trigger 3 times. Another example is the switching of the page, first determining the current page information, and then looking up to determine the page information of the previous page.
  • the previous page is recorded as empty, and then the page information of the next page is searched, and then sequentially statistics.
  • the statistical information corresponding to each parameter one or more collection parameters corresponding to each target application are determined; and the statistical data corresponding to each parameter is determined, and the test data corresponding to each parameter and the parameter is generated according to the applied classification.
  • Step 618 Analyze the running result of the collection tool in the target application according to the test report.
  • An acquisition tool is added to the target application to assist the target application in collecting the test information through the acquisition tool.
  • the test report can also be used to analyze the running result of the collection tool in the target application.
  • the running result includes at least one of the following: data collection results, data upload results, report generation results, and application running results.
  • the data collection result is the analysis of the collection parameters of the collection tool in the test equipment through the test report, such as whether it can be collected normally.
  • the result of data uploading is to analyze the parameter information of the collection tool in the test device through the test report, such as whether the upload is normal.
  • the report generation result is that after the test report analyzes the uploading parameter information of the collecting tool in the test device, the report is generated, that is, the parameter information can be generated by the normal statistical parameter information.
  • the application running result is to analyze the running status of the target application when the test device collects and uploads through the collection tool through the test report, such as whether the target application is running normally, whether there is a problem such as a stuck, a flashback, or a crash.
  • the target application is installed in the test device, and the application identifier is allocated to the target application, the test identifier is configured for the test device, and the collection parameter and the test identifier of the target application are used as the test information upload server, and the server uploads by analyzing multiple devices.
  • the data information is determined according to the test identifier, and the test information belongs to the test device, and the parameter information is statistically calculated, and the test report is generated according to the statistical result, and the test report can clearly reflect the current target application in the test device operation;
  • the test application auxiliary parameter information of the acquisition tool is installed in the target application, and the test report is used to analyze the operation of the collection tool in the target application.
  • the data analysis server 104 is further configured to search for verification parameter corresponding verification information from the parameter information, and analyze the verification information to determine a hijacking verification result.
  • the data analysis server 104 is configured to determine a parameter identifier of the verification parameter, search for the parameter identifier corresponding to the verification information from the parameter information, and detect whether the verification information is target information; If the target information is not used, it is determined that the traffic has a hijacking abnormality, and the hijacking abnormality is recorded in the hijacking verification result; if the verification information is the target information, it is determined that the data transmission is normal, and the recording transmission is normal in the hijacking verification result.
  • the method further includes: the data analysis server searching for the verification parameter corresponding to the verification information from the parameter information; and analyzing the verification information to determine the hijacking verification result.
  • the information is the target information, and it is determined that the data transmission is normal, and the recording transmission is normal in the hijacking verification result.
  • Step 702 Receive uploaded parameter information.
  • the parameter information is collected for each acquisition parameter when the application is running.
  • the acquisition control server determines the application to be collected based on the data that needs to be collected by each service platform.
  • the cloud server may determine the static parameters and the dynamic parameters of the application to be collected according to the application type, and set the collection configuration information, so that the terminals of the applications or applications can collect and upload the collected collections according to the collection configuration information.
  • the parameters correspond to the parameter information.
  • the uploaded parameter information may include: parameter information of the destination address returned by the host after the hijacking, and parameter information of the direct upload destination address.
  • the destination address belongs to the address list. In essence, the address list can be pre-set in the data analysis server.
  • the address list contains the IP addresses uploaded to the data analysis server, which is equivalent to the target address; and the address information corresponding to each IP address, which is equivalent to the target address information.
  • the target address can be used as the destination address.
  • the parameter information may be uploaded from the terminal where the application is located to the data analysis server. Therefore, the uploaded IP address can be recorded in the parameter information, and the parameter information of the upload destination address can be generated. For example, the last upload IP address is generated to generate LastIP information.
  • the parameter information of the upload destination address may include parameter information of directly uploading the destination address and parameter information of the destination address after the hijacking is returned.
  • Step 704 Determine a parameter identifier of the verification parameter, and search for the verification information corresponding to the parameter identifier from the parameter information.
  • the data analysis and analysis server may determine the verification parameter that needs to be verified according to the verification requirement. By determining the parameter identification of the verification parameter, the search can be performed according to the determined parameter identification. If the verification information corresponding to the determined parameter identifier is found from the parameter information, the found verification information may be extracted to detect whether the parameter information is intercepted during the transmission.
  • the analysis server B can extract the parameter information according to the IP address from the uploaded parameter information.
  • the LastIP information corresponding to the identifier of the IP address, and the LastIP information includes each IP address uploaded by the parameter information from the terminal A to the analysis server B, such as LastIP1, LastIP2, LastIP3, and the like.
  • Step 706 Detect whether the verification information is target information. If the verification information is not the target information, step 708 is performed; if the verification information is the target information, step 710 is performed.
  • the data analysis server may determine whether the parameter information is intercepted by detecting that the IP address information matches the target address information in the address list.
  • the foregoing step 706 may be to detect that the IP address information matches the target address information in the address list. Specifically, if the IP address corresponding to the IP address information extracted from the parameter information is not in the preset address list, that is, when the address list cannot find the target address corresponding to the extracted IP address information, the extracted IP is determined.
  • step 708 If the address information does not match the target address information in the address list, it may be determined that the parameter information is intercepted, and step 708 is performed. If the IP address corresponding to the IP address information extracted from the parameter information is in a preset list, that is, the IP address corresponding to the extracted IP address information can be found in the address list, the extracted IP address information and the address list are determined. If the target address information is matched, it can be determined that the parameter information is not intercepted, and step 710 is performed.
  • LastIP1, LastIP2, and LastIP3 can be found in the preset address list, it can be determined that the parameter information is not intercepted, and step 710 is performed; if the LastIP1 cannot be found in the address list, it can be determined that the parameter information is If the illegal terminal or the malicious program intercepts, and the IP address corresponding to the illegal terminal or the malicious program that intercepts the parameter information is LastIP1, step 708 is performed.
  • Step 708 determining that the traffic has a hijacking abnormality, and recording the hijacking abnormality in the hijacking verification result.
  • the data analysis server may determine that the traffic hijacking phenomenon exists in the parameter information uploading process, and the terminal parameter or the malicious program that may be intercepted by the intercepted parameter information may be tampered to determine the parameter.
  • the traffic corresponding to the information upload has a hijacking abnormality.
  • the hijacking abnormality of the parameter information is recorded in the hijacking verification result.
  • the parameter information is intercepted by the terminal of LastIP1 or the LastIP1 is recorded as an illegal IP address and a malicious IP address.
  • the data analysis results are generated, thereby avoiding the use of intercepted parameter information for statistics, and ensuring the accuracy of the data analysis results.
  • step 710 it is determined that the data transmission is normal, and the recording transmission is normal in the hijacking verification result.
  • the parameter information is not intercepted, it can be determined that the data transmission is normal, and the transmission of the parameter information in the hijacking verification result is normal, thereby ensuring the accuracy of the data analysis result.
  • the data analysis server 104 is further configured to search for storage parameter corresponding storage information from the parameter information, and determine a quality check result according to the stored information.
  • the data analysis server 104 is configured to determine a storage identifier of the storage parameter, search for the storage identifier corresponding storage information from the parameter information, and search for at least one terminal identifier according to the storage information; and when the storage information corresponds to one terminal Identifying, generating a quality-qualified quality check result; when the stored information corresponds to more than one terminal identifier, searching for the terminal identifier corresponding to the successful uploading information; sorting the terminal identifiers corresponding to the uploading success information, and determining the When there is no redundancy in the upload success information, the data is judged to be abnormal, and a quality check result of the data abnormality is generated.
  • the data terminal such as a mobile phone or a tablet computer collects application data through the collection tool, after collecting the parameter information corresponding to each acquisition parameter, the collected parameter information is uploaded, so that the data analysis is performed.
  • the server can receive the uploaded parameter information.
  • the parameter information may include storage information, verification information, information corresponding to the acquisition parameters, and the like.
  • the storage letter can be used to detect data quality and determine quality verification results, such as Secure Digital Memory Card information (SD card information), Multimedia Media Card (MMC) information, and SM card ( Smart Media Card information, CF card (Compact Flash Card) information, etc.; verification information can be used to analyze data transmission conditions and determine hijacking verification results, such as IP (Internet Protocol) address information.
  • SD card information Secure Digital Memory Card information
  • MMC Multimedia Media Card
  • SM card Smart Media Card information, CF card (Compact Flash Card) information, etc.
  • verification information can be used to analyze data transmission conditions and determine hijacking verification results, such as IP (Internet Protocol) address information.
  • the data analysis server may analyze the parameter information, and search for the storage parameter corresponding storage information from the parameter information.
  • preset storage parameters such as preset SD card parameters, may be set according to detection requirements.
  • the data analysis server uses the stored information to perform data quality detection on the parameter information, to determine whether the collected parameter information has data fraud, that is, to determine the accuracy of the collected parameter information, and determine the quality check result.
  • the method further includes: the data analysis server searching for the storage parameter corresponding storage information from the parameter information; detecting the data quality according to the stored information, and determining a quality check result.
  • the quality of the collected data can also be checked.
  • the quality verification steps for the transmitted data are as follows:
  • Step 802 Receive uploaded parameter information.
  • the parameter information is collected for each acquisition parameter when the application is running.
  • the acquisition control server determines the application to be collected based on the data that needs to be collected by each service platform.
  • the cloud server may determine the static parameters and the dynamic parameters of the application to be collected according to the application type, and set the collection configuration information, so that the terminals of the applications or applications can collect and upload the collected collections according to the collection configuration information.
  • the parameters correspond to the parameter information.
  • Step 804 determining a storage identifier of the storage parameter, and searching for the storage identifier corresponding storage information from the parameter information.
  • the data analysis and analysis server may determine the storage information that needs to be extracted according to the requirements of the data quality detection, and perform data quality detection on the parameter information by using the extracted storage information to determine whether the uploaded parameter information is abnormal. Specifically, by determining the storage identifier of the storage parameter, the search may be performed according to the determined parameter identifier; if the storage information corresponding to the determined storage identifier is found from the parameter information, the found storage information may be extracted, so as to The uploaded parameter information is used to detect the data quality, such as determining whether the uploaded parameter information is fraudulent data.
  • the storage parameters set by the data analysis server can include The SD card parameter
  • the storage parameter corresponding storage information may include SD card information.
  • the data analysis server may search for the received parameter information according to the SD card identifier by determining the SD card identifier, and extract the SD card identifier corresponding to the SD card information from the parameter information. It should be noted that each SD card has a unique corresponding SD card identifier, and the SD card information can be used to find the SD card identifier corresponding to the SD card.
  • Step 806 Find at least one terminal identifier according to the stored information.
  • the data quality detection may be performed according to the stored information, and it is determined whether the collected parameter information has data fraud. Specifically, extracting identification information of each terminal from all the received parameter information, and determining whether the terminal identifier of the extracted identification information corresponds to the extracted storage information; if the terminal identifier corresponds to the extracted storage information, The extracted storage information is the storage information of the terminal, and the corresponding relationship between the extracted storage information and the terminal identifier of the terminal is established.
  • terminal A, terminal B, and terminal C are connected to the same SD card, labeled as SD card 1, and the SD card information of SD card 1 is labeled as SD card information 1; terminal D is connected to another The SD card is labeled as SD card 2, and the SD card information of the SD card 2 is marked as SD card information 2.
  • the data analysis server extracts the SD card information from the parameter information uploaded by the terminal A, the terminal B, or the terminal C, the extracted SD card information is the SD card information 1, and the SD card identifier is found according to the SD card information 1, and the terminal can be found.
  • the SD card identifier corresponding to A, the SD card identifier corresponding to the terminal B, and the SD card identifier corresponding to the terminal C is used to search for the uploaded parameter information, and the three SD card identifiers corresponding to the SD card information 1 can be obtained.
  • the data analysis server extracts the SD card information from the parameter information uploaded by the terminal D, the extracted SD card information is the SD card information 2, and the SD card identifier is found according to the SD card information 2, and the SD card identifier corresponding to the terminal D can be found. That is, according to the SD card information 2, the uploaded parameter information is searched, and one SD card identifier corresponding to the SD card information 2 can be obtained.
  • Step 808 The terminal identifier is used to detect data quality, and the quality check result is determined.
  • the data analysis server may perform statistics on the terminal identifier corresponding to the stored information, determine the number of the terminal identifier corresponding to the storage information, and determine whether the stored information belongs to a terminal based on the number of the terminal identifier, which is equivalent to determining the storage information. Whether the corresponding parameter information has data fraud. If the number of the terminal identifiers corresponding to the stored information is 1, the stored information belongs to one terminal. In the above example, the SD card information 2 belongs to the terminal D, and it can be determined that the collected data is normal, that is, the SD card information 2 is determined.
  • the parameter information is not falsified data, and the quality verification result that the quality of the data collection is qualified is generated. If the number of terminal identifiers corresponding to the stored information is not 1, the stored information does not belong to one terminal.
  • the SD card information 1 belongs to three terminals, and the collected data may be abnormal, that is, the SD card information 1
  • the corresponding parameter information may be fraudulent data, and a quality check result of the data abnormality is generated.
  • a quality qualified quality verification result is generated.
  • a quality check result of the data abnormality is generated.
  • the data analysis server may determine that the parameter information corresponding to the storage information is normal data, and may use the parameter information to perform data analysis, and generate a data report required by each service platform to understand Business needs, adjustments to the business.
  • searching for the terminal identifier corresponding to the successful uploading information searching for the terminal identifier corresponding to the successful uploading information; sorting each terminal identifier corresponding to the uploading success information; determining, according to the sorting result, that the uploading success information does not exist redundantly In the remaining time, the data is judged to be abnormal.
  • some terminal devices such as monitors, have no storage space locally, and connect to the processor or hard disk to process data using the storage space of the processor or hard disk.
  • the multiple terminals can share the same processor or the storage space of the hard disk to process data.
  • multiple displays are connected to the same SD card, that is, the storage space of the same SD card is shared.
  • data collection is performed on multiple terminals connected to the same hard disk or processor, and the parameter information collected in essence is data of the same hard disk or processor.
  • the data analysis server may search for the successful upload information corresponding to each terminal identifier, such as successfully transmitting log information (transformation).
  • the successfully uploaded information corresponding to the terminal identifier includes the number of successful transmissions, such as the number of times the transmission log is successfully transmitted (referred to as the tt value). Each time the parameter information collected is successfully uploaded, the tt value is automatically increased according to the unit value, such as automatically incremented by 1.
  • the data analysis server may sort the upload success information corresponding to each terminal identifier, such as sorting according to the size of the tt value, and determine whether the upload success information is redundant based on the sorting result.
  • the data analysis server sorts the number of successfully transmitted logs according to the size of the tt value, and determines whether the number of successfully transmitted logs is repeated; when the number of successfully transmitted logs is not repeated If there is no redundancy in the number of times the log is successfully transmitted, the data may be abnormal.
  • the tt value of the SD card corresponding to the terminal A is 1, the tt value of the SD card corresponding to the terminal B is 3, and the terminal C
  • the tt value of the corresponding SD card identifier is 2, that is, there is no redundancy in the number of times of successfully transmitting the log, and it can be determined that the parameter information including the SD card information 1 is abnormal, which is equivalent to determining that the parameter information including the SD card information 1 has data fraud, and generates
  • the quality check result of the data abnormality avoids the parameter information for data analysis, that is, avoids using abnormal parameter information for analysis, and improves the accuracy of data collection.
  • the data analysis server may determine that the data is abnormal, and generate a quality check result of the data abnormality, so as to avoid using abnormal data for data analysis, and ensuring data analysis results. accuracy.
  • modules or units or components of the embodiments may be combined into one module or unit or component, and further they may be divided into a plurality of sub-modules or sub-units or sub-components.
  • any combination of the features disclosed in the specification, including the accompanying claims, the abstract and the drawings, and any methods so disclosed, or All processes or units of the device are combined.
  • Each feature disclosed in this specification may be replaced by alternative features that provide the same, equivalent or similar purpose.
  • the various component embodiments of the present invention may be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof.
  • a microprocessor or digital signal processor DSP
  • the invention may also be embodied as a device or device program for performing some or all of the methods described herein (eg, Computer programs and computer program products).
  • Such a program implementing the invention may be stored on a computer readable medium or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.
  • Figure 9 illustrates a computing device that can implement a data acquisition analysis method in accordance with the present invention.
  • the computing device conventionally includes a processor 910 and a program product or readable medium in the form of a memory 920.
  • Memory 920 can be an electronic memory such as a flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, or ROM.
  • Memory 920 has a memory space 930 for program code 931 for performing any of the method steps described above.
  • storage space 930 for program code may include various program code 931 for implementing various steps in the above methods, respectively.
  • These program codes can be read from or written to one or more program products.
  • These program products include program code carriers such as memory cards.
  • Such a program product is typically a portable or fixed storage unit as described with reference to FIG.
  • the storage unit may have storage segments, storage spaces, and the like that are similarly arranged to memory 920 in the computing device of FIG.
  • the program code can be compressed, for example, in an appropriate form.
  • the storage unit includes readable code 931', ie, code that can be read by a processor, such as 910, which, when executed by a computing device, causes the computing device to perform various steps in the methods described above. .

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Mining & Analysis (AREA)
  • Debugging And Monitoring (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

一种数据采集分析系统和方法,所述系统包括:采集控制服务器、数据分析服务器、报表生成服务器和至少一个数据终端,数据终端中安装有采集工具;采集控制服务器,用于配置采集配置信息给数据终端并下发给相应的数据终端;数据终端,用于在应用运行时调用采集工具,依据采集配置信息对采集参数的参数信息进行采集;以及将采集的参数信息上传给数据分析服务器;数据分析服务器,用于对上传的各采集参数对应参数信息进行分析,获取数据分析结果;将数据分析结果发送给报表生成服务器;报表生成服务器,用于依据数据分析结果生成数据报表;通过该数据报表获知用户需求、习惯等,对业务进行调整,更符合用户需求。

Description

一种数据采集分析系统和方法 技术领域
本发明涉及数据处理技术领域,特别是涉及一种数据采集分析方法、一种数据采集分析系统、一种程序和一种可读介质。
背景技术
随着通信技术的快速发展,尤其是随着移动互联网的推广,智能终端的普及越来越快,且智能终端的功能也越来越丰富。其中,智能终端通过安装各种各样的应用实现其功能,提供多样化的服务。
为了提高服务质量,各服务平台的开发人员需要设置的数据采集方案采集应用的数据,以了解业务需求。其中,不同的业务需要采集的应用数据不同。因此,服务平台的开发人员需要根据不同的业务设置不同的应用数据采集方案。具体的,服务平台的开发人员需要根据服务平台提供的业务,设置各应用的采集参数,按照设置的采集参数对各应用进行数据采集,生成该服务平台的业务报表,以了解业务需求。但是,安装在智能终端上的应用比较多,即需要采集的应用数据比较多,导致各服务平台的数据采集格式难以统一。因此,各服务平台的开发人员还需要定义各应用的数据采集格式,使得各服务平台可以按照设置的数据采集格式采集各应用的数据,进一步增加开发人员的工作量。
发明内容
鉴于上述问题,提出了本发明以便提供一种克服上述问题或者至少部分地解决上述问题的数据采集分析方法和相应的数据采集分析系统。
依据本发明的一个方面,提供了一种数据采集分析系统,包括:采集控制服务器、数据分析服务器、报表生成服务器和至少一个数据终端,所述数据终端中安装有采集工具;所述采集控制服务器,用于配置采集配置信息给数据终端并下发给相应的数据终端,其中,所述采集配置信息用于控制采集参数的采集;所述数据终端,用于在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集;以及将采集的参数信息上传给所述数据分析服务器;所述数据分析服务器,用于对上传的各采集参数对应参数信息进行分析,获取数据分析结果;将所述数据分析结果发送给所述报表生成服务器;所述报表生成服务器,用于依据所述数据分析结果生成数据报表。
根据本发明的另一方面,提供了所述数据采集分析方法应用于数据采集分析系统中,数据采集分析系统包括:所述采集控制服务器、数据分析服务器、报表生成服务器和至少一个数据终端,所述数据终端中安装有采集工具;所述的方法包括:所述采集控制服务器配置采集配置信息给数据终端并下发给相应的数据终端;所述数据终端在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集;所述数据终端将采集的参数信息上传给所述采集控制服务器;所述数据分析服务器对上传的各采集参数对应参数信息进行分析,获取数据分析结果;所述数据分析服务器将所述数据分析结果发送给所述报表生成服务器;所述报表生成服务器依据所述数据分析结果生成数据报表。
根据本发明的又一方面,提供了一种程序,包括可读代码,当所述可读代码在计算设备上运行时,导致所述计算设备执行根据本发明实施例中的任一个所述的数据采集分析方法。
本发明实施例还提供了一种可读介质,其中存储了如本发明实施例所述的程序。
应用启动并进行初始化时调用采集工具,采用该采集工具对应用进行数据采集时,采集工具可以依据采集配置信息采集所述应用中各采集参数的参数信息。采集工具采集所述应用中各采集参数的参数信息后,判断是否满足上传条件,若满足,采集工具按照预置算法将参数信息进行压缩,然后上传给数据分析服务器。数据分析服务器对上传的各采集参数对应参数信息进行分析,如对各采集参数对 应的参数信息进行统计,从而获取数据分析结果,再将所述数据分析结果发送给所述报表生成服务器,所述报表生成服务器依据所述数据分析结果,为各逻辑的数据分析结果配置可读的属性信息生成数据报表,从而可以基于该数据报表确定应用的使用情况。从而通过采集工具能够在应用运行的数据终端中采集各采集参数的参数信息,在上传给数据分析服务器后,依据统计需求进行数据分析,从而生成相应业务的数据报表,通过该数据报表获知用户需求、习惯等,对业务进行调整,更符合用户需求。
上述说明仅是本发明技术方案的概述,为了能够更清楚了解本发明的技术手段,而可依照说明书的内容予以实施,并且为了让本发明的上述和其它目的、特征和优点能够更明显易懂,以下特举本发明的具体实施方式。
附图说明
通过阅读下文优选实施方式的详细描述,各种其他的优点和益处对于本领域普通技术人员将变得清楚明了。附图仅用于示出优选实施方式的目的,而并不认为是对本发明的限制。而且在整个附图中,用相同的参考符号表示相同的部件。在附图中:
图1示出了根据本发明一个实施例的数据采集分析系统结构框图;
图2示出了根据本发明一个实施例的数据采集分析方法的步骤流程图;
图3示出了根据本发明另一个实施例的数据采集分析系统结构框图;
图4示出了根据本发明另一个实施例的数据采集分析方法的步骤流程图;
图5示出了根据本发明另一个实施例的自定义事件处理方法的步骤流程图;
图6示出了根据本发明另一个实施例的目标应用的测试方法的步骤流程图;
图7示出了根据本发明另一个实施例的传输校验方法的步骤流程图;以及
图8示出了根据本发明另一个实施例的数据质量校验方法的步骤流程图;
图9示出了用于执行根据本发明的数据采集分析方法的计算设备的框图;
图10示出了用于保持或者携带实现根据本发明的数据采集分析方法的程序代码的存储单元。
具体实施方式
下面将参照附图更详细地描述本公开的示例性实施例。虽然附图中显示了本公开的示例性实施例,然而应当理解,可以以各种形式实现本公开而不应被这里阐述的实施例所限制。相反,提供这些实施例是为了能够更透彻地理解本公开,并且能够将本公开的范围完整的传达给本领域的技术人员。
通常,一些终端如手机、平板电脑的供应商、软件开发商通过采集安装在终端上的应用在运行时的数据,并对采集的数据进行分析,生成业务报表,以了解业务需求。本发明实施例提供了一种数据采集分析系统,该系统具有通用性,能够为各种应用采集、分析数据并生成不同的业务报表。
参照图1,示出了根据本发明一个实施例的数据采集分析系统结构框图。
该数据采集分析系统,包括:采集控制服务器102、数据分析服务器104、报表生成服务器106和至少一个数据终端108,所述数据终端中安装有采集工具。所述采集控制服务器102,用于配置采集配置信息给数据终端并下发给相应的数据终端,其中,所述采集配置信息用于控制采集参数的采集;所述数据终端108,用于在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集;以及将采集的参数信息上传给所述数据分析服务器;所述数据分析服务器104,用于对上传的各采集参数对应参数信息进行分析,获取数据分析结果;将所述数据分析结果发送给所述报表生成服务器;所述报表生成服务器106,用于依据所述数据分析结果生成数据报表。
基于上述数据采集分析系统,相应的数据采集分析方法的步骤如下:
参照图2,示出了根据本发明一个实施例的数据采集分析方法的步骤流程图。
步骤202,所述采集控制服务器配置采集配置信息给数据终端并下发给相应的数据终端。
步骤204,所述数据终端在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集。
步骤206,所述数据终端将采集的参数信息上传给所述采集控制服务器。
步骤208,所述数据分析服务器对上传的各采集参数对应参数信息进行分析,获取数据分析结果。
步骤210,所述数据分析服务器将所述数据分析结果发送给所述报表生成服务器。
步骤212,所述报表生成服务器依据所述数据分析结果生成数据报表。
本发明实施例的应用是指安装在终端上的应用程序,如手机助手、浏览器、安全卫士、播放器等。为了保证采集数据的完整性和准确性,可以在应用运行时调用采集工具。采集工具包括软件开发工具包(SDK,Software Development Kit)。针对不同的应用以及应用所在终端,采集控制服务器可以配置各应用的采集参数以及采集配置信息,生成采集工具的控制信息。当应用所在终端调用采集工具对应用进行数据采集时,采集工具可以依据采集配置信息采集所述应用中各采集参数的参数信息。其中,所述采集配置信息用于控制所述采集参数的采集和上传。所述采集参数包括静态参数和/或动态参数。该静态参数可以用于采集该应用所对应的静态的参数信息;动态参数可以用于采集该应用运行时的动态的参数信息。应用启动并进行初始化时调用采集工具,采用该采集工具对应用进行数据采集时,采集工具可以依据采集配置信息采集所述应用中各采集参数的参数信息。采集工具采集所述应用中各采集参数的参数信息后,判断是否满足上传条件,若满足,采集工具按照预置算法将参数信息进行压缩,然后上传给数据分析服务器。数据分析服务器对上传的各采集参数对应参数信息进行分析,如对各采集参数对应的参数信息进行统计,从而获取数据分析结果,再将所述数据分析结果发送给所述报表生成服务器,所述报表生成服务器依据所述数据分析结果,为各逻辑的数据分析结果配置可读的属性信息生成数据报表,从而可以基于该数据报表确定应用的使用情况。从而通过采集工具能够在应用运行的数据终端中采集各采集参数的参数信息,在上传给数据分析服务器后,依据统计需求进行数据分析,从而生成相应业务的数据报表,通过该数据报表获知用户需求、习惯等,对业务进行调整,更符合用户需求。
参照图3,示出了根据本发明另一个实施例的数据采集分析系统结构框图。所述采集控制服务器102包括云控服务器1022;所述云控服务器1022,用于依据应用类型确定所述应用的采集参数,其中,所述采集参数包括:动态参数和/或静态参数;依据所述应用和应用所在终端配置采集配置信息,其中,所述采集配置信息用于控制所述采集参数的采集和上传;将采集参数和采集配置信息下发给应用所在的数据终端。所述云控服务器1022,用于配置参数信息的上传条件和/或采样条件,将上传条件和/或采样条件添加到采集配置信息中;配置所述应用所在终端对应内存的采集阈值,将所述采集阈值添加到采集配置信息中;配置所述应用所在终端对应网络类型的上传间隔,将所述上传间隔添加到所述采集配置信息中;配置所述应用所在终端对应缓存阈值,将所述缓存阈值添加到采集配置信息中;以及,在所述采集配置信息中配置协议上传顺序、采样率和采样参数的优先级。所述数据终端108,用于采用采集工具依据采集配置信息采集所述应用的静态参数的参数信息;以及,采用所述采集工具依据采集配置信息确定待采集的动态参数,依据所述应用的运行实时采集所述动态参数的参数信息。所述数据终端108,用于当检测到所述应用的界面切换时,记录切换前的界面为上一页,记录切换后的界面为当前页,将所述上一页和当前页添加到应用界面启动信息中;当检测到所述应用的按钮被触发时,获取所述按钮对应的按钮编号,更新所述按钮编号对应的点击次数,将所述按钮编号和点击次数添加到按钮点击信息中;采集所述应用相关的运行时间作为时长信息,其中,所述时长信息 包括:界面运行时间和应用运行时间。
基于上述数据采集分析系统,可以在数据终端中应用运行时对参数信息的采集、上传分析生成相应的报表,具体步骤如下:
参照图4,示出了根据本发明另一个实施例的数据采集分析方法的步骤流程图。
步骤402,所述采集控制服务器依据应用类型确定所述应用的采集参数。实质上,针对不同的应用以及应用所在终端,云服务器可以配置各应用的采集参数以及采集配置信息,生成采集工具的控制信息。当应用所在终端通过调用采集工具对应用进行数据采集时,云服务器就可以通过采集工具的控制信息控制应用所在终端对各应用的数据采集。其中,所述采集参数包括:动态参数和/或静态参数。所述静态参数的参数信息包括以下至少一项:终端标识、版本信息、渠道信息、网络类型和分辨率信息;所述动态参数的参数信息包括以下至少一项:应用界面启动信息、按钮点击信息、时长信息、异常信息和会话信息。静态参数可以用于采集该应用对应的静态参数信息,如应用所在终端的标识信息、版本信息、渠道信息、网络类型和分辨率信息等。其中,终端的标识信息可以用于识别应用所在终端,如可以基于终端的硬件等信息计算M2值,该M2值可以通过序列号、机型号、版本信息等计算,该M2值既能够标识不同的终端又不会泄露终端的硬件信息,保证用户的隐私安全;版本信息可以用于记录该应用对应的版本,如终端的操作系统版本,软件版本或者软件开发工具包版本等;渠道信息可以用于识别该应用的获取路径;网络类型用于确定应用所在终端连接的网络类型;分辨率信息用于确定该应用所在终端的显示分辨率,显示分辨率又可以称为屏幕分辨率。动态参数可以用于采集该应用在运行过程中生成的参数信息,如应用界面启动信息、按钮点击信息、时长信息、异常信息和会话信息等。其中,应用界面启动信息用于记录应用的界面切换时切换前的页面以及切换后的界面;按钮点击信息用于记录用户点击该应用中各按钮对应的按钮编号以及该按钮编号对应的点击次数;时长信息根据启动时间点和关闭时间点确定,如应用运行时间、界面运行时间;异常信息用于记录应用运行异常的信息,如应用启动失败的时间点或者次数;会话信息用于记录该应用在运行时产生的会话类的消息。
步骤404,所述采集控制服务器依据所述应用和应用所在终端配置的采集配置信息。依据所述应用和应用所在终端配置的采集配置信息的步骤包括以下至少一种:配置参数信息的上传条件和/或采样条件,将上传条件和/或采样条件添加到采集配置信息中;配置所述应用所在终端对应内存的采集阈值,将所述采集阈值添加到采集配置信息中;配置所述应用所在终端对应网络类型的上传间隔,将所述上传间隔添加到所述采集配置信息中;配置所述应用所在终端对应缓存阈值,将所述缓存阈值添加到采集配置信息中;在所述采集配置信息中配置协议上传顺序、采样率和采样参数的优先级。
步骤406,所述采集控制服务器将采集参数和采集配置信息下发给应用所在的数据终端。其中,所述采集配置信息用于控制所述采集参数的采集和上传。在具体实现中,按照采集配置信息对应用以及应用所在终端进行数据采集,并且需要按照采集配置信息中上传采集到的数据。因此,云服务器可以依据待采集的应用以及该应用所在终端,设置采集配置信息,使得各应用或者应用的终端可以按照该采集配置信息采集、上传采集参数。其中,所述上传条件用于依据上传成功标记位控制参数信息的上传,所述采样条件用于依据测试标识控制参数信息的采集。云服务器可以通过设置采样条件,并将采样条件添加到采集配置信息中,使得应用所在终端依据采集配置信息中的采样条件对应用进行数据采集。具体的,通过检测,可以确定应用的数据是否符合采样条件。例如,当应用具有测试标识时,该应用的全部参数信息符合采样条件,采集工具获取该应用中各静态参数的参数信息和动态参数的参数信息。例如,开发人员在维护应用过程中,依据需求等不断更新应用的版本,其中一些版本为测试版即Beta版,在测试通过后才会上线正式版,针对应用的Beta版即可配置测试标识,从而采集更多 甚至全部参数,以测试应用运行情况。在采集到参数信息后,还可以将采集到的参数信息缓存在本地。在参数信息满足采样配置信息中的上传条件时,将该参数信息进行上传。例如,云服务器可以通过设置各参数信息上传的优先级或者上传间隔,设置各参数信息的上传条件,并将该上传条件保存到采集配置信息中。在当前时刻达到参数信息的上传间隔时间时,应用所在终端可以将该参数信息进行压缩后,上传给云服务器,即将满足上传条件的参数信息上传。显然,云服务器可以针对不同的参数信息设置上传条件,并添加到采集配置信息中,进而可以通过该上传条件控制各参数信息的上传。配置所述应用所在终端对应内存的采集阈值,将所述采集阈值添加到采集配置信息中。其中,采集阈值用于依据终端的内存信息确定采集的采集参数。在本发明实施例中,考虑到不同类型的终端配置不同,有些终端内存较大如内存达到2G,而有些终端内存较小,为了减少数据采集对终端的影响,使得终端能够正常运行应用,云服务器可以根据应用所在终端的内存设置采集阈值,并将该采集阈值添加到采集配置信息中,从而可以依据终端的内存信息控制采集的采集参数。例如采集阈值配置为50M,则当终端的内存小于50M时,为了不影响终端的使用可以限制采集参数的采集,如不采集动态参数,仅采集终端标识等静态参数上传一次即可。作为本发明的一个具体示例,当应用所在终端的内存信息未达到采集阈值时,可以不采集安装该终端上的应用的动态参数对应的参数信息,可以采集静态参数对应的参数信息,如采集终端标识;当终端的内存信息达到采集阈值,则按照采集配置信息采集应用中各采集参数的参数信息,如采集应用中静态参数的参数信息和动态参数的参数信息。配置所述应用所在终端对应网络类型的上传间隔,将所述上传间隔添加到所述采集配置信息中。其中,所述上传间隔为定时上传的间隔,如5分钟、10分钟等。实质上,通过不同类型的网络传输数据,数据的传输速率不一样。因此,可以根据网络类型对应的数据传输速率,设置应用所在终端对应网络类型的上传间隔,并将不同网络类型的上传间隔添加到采集配置信息中。
在本发明实施例中,可以根据应用所在终端连接的网络类型,选择该网络类型对应的上传间隔,使得各应用可以依据当前连接网络的数据传输速率上传采集参数的参数信息,从而可以充分利用了网络资源,并且保证参数信息的上传速率。本实施例中,上传间隔可以依据网络类型和采集参数本身的优先级来确定。配置所述应用所在终端对应缓存阈值,将所述缓存阈值添加到采集配置信息中。其中,缓存阈值用于确定在终端的缓存的参数信息的数据量。具体而言,不同的终端的性能不同,因此其可以缓存的参数信息的数据量不同。根据应用所在终端可以缓存的数据量,可以设置该终端对应的缓存阈值,并将该缓存阈值添加到采集配置信息中。当终端的本地缓存的参数信息超过缓存阈值时,云服务器可以控制终端删除缓存时间在前的参数信息,直到缓存的参数信息不超过所述缓存阈值,保证了数据采集的效率。例如设置缓存阈值为2M,在采集参数信息要存储时判断本地缓存已超过2M,则可以按照时间的前后顺序,从前面开始删除参数信息,直到存储该采集参数也不超过2M为止。在所述采集配置信息中配置协议上传顺序、采样率和采样参数的优先级。其中,所述协议上传顺序用于确定采集参数的上传协议,所述采样率用于确定采样的终端,所述优先级用于确定参数信息的采集次数和上传间隔。在具体实现中,云服务器可以对网络所采用的网络传输协议进行统计,确定各网络传输协议的优先级,生成协议上传顺序。例如,协议上传顺序可以如下:1、传输控制协议(Transmission Control Protocol,TCP);2、无线应用协议(Wireless Application Protocol,WAP);3、用户数据报协议(User Datagram Protocol,UDP);4、实时传输协议(Real-time Transport Protocol,RTP);5、超文本传输协议(HTTP,HyperText Transfer Protocol)。其中,网络传输协议对应的顺序编号可以代表了该网络传输协议的优先级,顺序编号越小代表该网络传输协议的优先级越高,如1代表TCP协议的优先级最高。将协议上传的顺序添加到采集配置信息中,就可以控制参数信息上传时所采用的网络传输协议,如上述例子的协议上传顺序,参数信息优选采用优先级最高的TCP协议上传,当不可以 采用TCP协议上传时采用WAP协议上传,即按照优先级的顺序选择上传协议,避免由于终端、应用不支持采用某一网络传输协议而导致参数信息上传失败的问题,保证参数信息的上传效率和上传质量。
当终端比较多的时候,云服务器可以对应用所在终端进行统计,确定采样率。通过采样率,可以确定待采样的终端数量,并且可以按照所确定的终端数量随机选取应用所在终端,将选取的终端作为目标终端,以及确定为采样的终端。作为本发明的一个具体示例,可以通过预置的算法对各终端的终端标识进行计算,选取目标终端,如通过终端标识的最后一位或两位的数字,确定目标终端。当然,云服务器还可以通过其他方式确定采样的终端,如通过对终端标识进行取模或者取余等运算确定采样的终端,本发明实施例对此不作限制。通过将采样率添加到采样配置信息中,云服务器可以控制采样的终端数量,避免采样大量的终端而造成云端服务器数据处理压力大的问题,保证数据的采样效率,进而加快数据采集的进度。云服务器还可以通过设置各采集参数的优先级,控制采集参数的参数信息的采集次数和上传间隔。例如,参照表1,当应用或应用所在终端确定采集参数的优先级,就可以依据所确定的优先级对应的采集次数对该采集参数的信息进行采集,并按照该优先级对应的上传间隔上传该采集参数的参数信息,如采集参数I的优先级为A级,则该采集参数I的参数信息的采集次数为1000次,且上传间隔为20分钟,即每隔20分钟,就上传一次该采集参数I的参数信息。
采集参数的优先级 参数信息的采集次数 参数信息的上传间隔
A级 1000次 20分钟
B级 700次 1小时
C级 300次 3小时
D级 10次 12小时
F级 1次 24小时
表1
在本发明实施例中,可以根据业务需求或者采集数据的特性,预先设置采集参数的优先级,以及各优先级对应的参数信息采集次数和上传间隔,使得云服务器可以通过将采集参数的优先级添加到采集配置信息中,控制应用或者应用所在终端按照采样参数的优选级对参数信息进行采集以及上传。通过采集参数的优先级,可以及时采集到各应用采集参数的参数信息,并且还可以及时将采集到的参数信息上传。
步骤408,采用所述采集工具依据采集配置信息采集所述应用的静态参数的参数信息。
步骤410,采用所述采集工具依据采集配置信息确定待采集的动态参数,依据所述应用的运行实时采集所述动态参数的参数信息。
依据所述采集控制服务器下发的采集配置信息,可以在应用运行时对采集参数进行采集,包括:依据所述配置信息中各采集参数的优先级,确定所述采集参数的参数信息的采集次数和上传间隔。获取所述应用所在移动终端的内存信息,判断所述内存信息是否达到采集阈值;当所述内存信息未达到采集阈值时,采集所述静态参数的采集参数上传给所述服务器,以结束采集步骤;当所述内存信息达到采集阈值时,应用运行时调用采集工具采集所述应用中各采集参数的参数信息,其中,所述采集参数包括静态参数和/或动态参数。在本发明实施例中,考虑到不同类型的终端配置不同,有些终端内存较大如内存达到2G,而有些终端内存较小,为了减少数据采集对终端的影响,使得终端能够正常运行应用,云服务器可以根据应用所在终端的内存设置采集阈值,并将该采集阈值添加到采集配置信息中,从而可以依据终端的内存信息控制采集的采集参数。当应用所在终端的内存信息未达到采集阈 值时,可以不采集安装该终端上的应用的动态参数对应的参数信息,可以采集静态参数对应的参数信息,如采集终端标识;例如采集阈值配置为50M,则当终端的内存小于50M时,为了不影响终端的使用可以限制采集参数的采集,如不采集动态参数,仅采集终端标识等静态参数上传一次即可。依据所述应用的运行实时采集所述动态参数的参数信息的步骤包括以下至少一种:
当检测到所述应用的界面切换时,记录切换前的界面为上一页,记录切换后的界面为当前页,将所述上一页和当前页添加到应用界面启动信息中。即在对用户在应用界面中访问记录时,为了保证访问的连续,可以在记录当前界面的同时记录上一访问界面,从而每一个界面记录均为当前页+上一页,当然若是首页,则上一页为空。
当检测到所述应用的按钮被触发时,获取所述按钮对应的按钮编号,更新所述按钮编号对应的点击次数,将所述按钮编号和点击次数添加到按钮点击信息中。应用中可以包括许多按钮,可以给每个按钮进行编号来标识不同的按钮,从而在按钮被点击时记录按钮编号以及点击次数,即点击次数初始为0,每点击一次即加一。
应用可以通过多进程方式运行,通常多进程运行时应用启动采用主进程记录启动时间点,采用最后一个进程记录结束时间点,但是,当应用启动时间过短时可能出现主进程未完全启动则应用已关闭的问题,此时记录的运行时间就可能为负值,或者采用上次启动的启动时间点与本次关闭的结束时间点计算时长,则会出现时长超长的情况,导致时长记录不准确。为解决上述不准确的问题,采集所述应用相关的运行时间作为时长信息,其中,所述时长信息包括:界面运行时间和应用运行时间。其中,所述采集所述应用相关的运行时间作为时长信息包括:所述应用的主进程记录启动时间点和结束时间点,依据所述启动时间点和结束时间点记录运行时间,将所述运行时间作为时长信息。即本实施例针对多进程运行的应用,开始和结束时间的记录均从采用主进程进行记录,即应用启动时采用主进程记录启动时间点,应用关闭是采用主进程记录结束时间点,从而计算结束时间点和启动时间点的差值即为运行时间,确保准确记录运行时长。此外,本发明实施例中为了节省用户流量等资源,可以将采集的参数信息缓存在本地,为了减少对数据终端的应用,可以配置缓存阈值,该缓存阈值用于确定在终端的缓存的参数信息的数据量。具体而言,不同的终端的性能不同,因此其可以缓存的参数信息的数据量不同。根据应用所在终端可以缓存的数据量,可以设置该终端对应的缓存阈值,并将该缓存阈值添加到采集配置信息中。当终端的本地缓存的参数信息超过缓存阈值时,云服务器可以控制终端删除缓存时间在前的参数信息,直到缓存的参数信息不超过所述缓存阈值,保证了数据采集的效率。例如设置缓存阈值为2M,在采集参数信息要存储时判断本地缓存已超过2M,则可以按照时间的前后顺序,从前面开始删除参数信息,直到存储该采集参数也不超过2M为止。
步骤412,所述数据终端将采集的参数信息上传给所述采集控制服务器。在进行参数信息的上传时,可以首先确定是否达到上传间隔,其中上传间隔处理依据参数优先级确定之外,还可以依据当前的网络类型确定上传间隔,判断当前时刻是否满足上传间隔。为了提高上传的成功率,还可以配置上传阈值,即每次上传数据量的阈值,检测当前缓存的参数信息是否大于上传阈值。在参数信息满足采样配置信息中的上传条件时,将该参数信息进行上传。例如,云服务器可以通过设置各参数信息上传的优先级或者上传间隔,设置各参数信息的上传条件,并将该上传条件保存到采集配置信息中。在当前时刻达到参数信息的上传间隔时间时,检测所述参数信息是否超过上传阈值。本发明实施例向服务器上传参数信息是通过数据包上传。若一个数据包包含的数据量过大,容易造成上传失败。本发明实施例通过上传阈值,来限制每次上传数据包的大小。当需要上传的参数信息超过上传阈值时,就采取分包的措施,即将所述参数信息划分为至少两个数据包。分包上传,可以避免数据量过大造成的上传失败。例如上传阈值为100k时,当需要上传的参数信息大于100k,可以将参数信息划分为至少两个 数据包,例如需要上传的参数信息为250k,则可以分成三个数据包100k、100k以及50k。然后,将所述参数信息按照预置算法进行压缩编码,生成参数数据包。依据预置协议上传顺序选择上传协议,依据所述上传协议向服务器上传参数信息。另外,参数信息上传给服务器时,可能会出现上传失败。此时可能需要将未上传的参数信息继续上传,为了便于区分参数信息的上传情况,可以依据上传结果配置上传成功标记位。通过上传成功标记位来标识上传结果。其中,若所述缓存的参数信息上传失败则配置上传成功标记位为失败,若所述缓存的参数信息上传成功则配置上传成功标记位为成功。在所述应用所在移动终端解锁时,对上传成功标记位进行检测。若所述上传成功标记为失败,获取当前的网络类型,判断所述网络类型是否允许上传数据。在确定上传成功标记为失败时,说明参数信息未上传成功,则可以获取当前的网络类型,判断网络类型是否允许上传数据,如网络是否连接,已连接的情况下判断为2G、3G、4G或WIFI等。若是,即所述网络类型允许上传数据时,将未上传的参数信息上传给所述服务器。若否,即网络类型不允许上传数据,在下次解锁后重新检测上传。为了节省资源,在所述应用下一次运行时如在所述应用所在移动终端解锁时,对上传成功标记位进行检测,判断参数信息的上传情况。若所述上传成功标记为失败,获取当前的网络类型,判断所述网络类型是否允许上传数据,在所述网络类型允许上传数据时,执行将未上传的参数信息上传给所述服务器的步骤。
步骤414,所述数据分析服务器对上传的各采集参数对应参数信息进行分析,获取数据分析结果。
步骤416,所述数据分析服务器将所述数据分析结果发送给所述报表生成服务器。
步骤418,所述报表生成服务器依据所述数据分析结果生成数据报表。数据分析服务器对上传的各采集参数对应参数信息进行分析,如对各采集参数对应的参数信息进行统计,从而获取数据分析结果,再将所述数据分析结果发送给所述报表生成服务器,所述报表生成服务器依据所述数据分析结果,为各逻辑的数据分析结果配置可读的属性信息生成数据报表,从而可以基于该数据报表确定应用的使用情况。通过在应用运行时调用采集工具;采集工具采集所述应用中各采集参数的参数信息;依据当前的网络类型确定上传间隔,判断当前时刻是否满足上传间隔;在当前时刻达到所述上传间隔时,将所述参数信息按照预置算法进行压缩编码,生成参数数据包;将所述参数数据包上传给服务器,以使所述服务器依据所述参数信息进行数据分析。从而减少了各服务平台的开发人员的工作量,进而降低用人成本,在各种应用中均可以使用,可扩展性较好。
本实施例中,所述报表生成服务器106,用于依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表。对事件进行统计时,往往只能对通用事件进行统计,通用事件只能对共有的特征进行统计,而对于一些特有的特征采用通用事件进行统计,统计效果不明显。而本实施例中,为使报表能够适应各种业务的需求,将终端上的各个应用对应需要统计的业务进行自定义,生成自定义事件,并依据各个应用对应自定义事件配置自定义管理信息。所述报表生成服务器106,还用于从所述业务管理页面中获取所述应用的应用路径,以及所述应用对应自定义事件的自定义事件信息,其中,所述自定义事件信息包括:事件名称和事件属性;采用所述应用路径和自定义事件信息生成自定义管理信息。所述报表生成服务器106,用于依据所述应用路径确定应用;针对每个自定义事件,获取所述事件名称对应的逻辑名称,以及所述事件属性对应的逻辑属性;查找所述逻辑名称对应采集参数,依据所述逻辑属性确定所述采集参数对应的业务统计信息;以及确定各采集参数对应的事件名称,采用各事件名称和对应采集参数的业务统计信息生成应用的自定义事件报表。所述报表生成服务器依据所述数据分析结果生成数据报表,包括:所述报表生成服务器依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表。还包括配置自定义管理信息的步骤:从所述业务管理页面中获取所述应用的应用路径,以及所述应用对应自定义事件的自定义事件信息,其中, 所述自定义事件信息包括:事件名称和事件属性;采用所述应用路径和自定义事件信息生成自定义管理信息。依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表,包括:依据所述应用路径确定应用;针对每个自定义事件,获取所述事件名称对应的逻辑名称,以及所述事件属性对应的逻辑属性;查找所述逻辑名称对应采集参数,依据所述逻辑属性确定所述采集参数对应的业务统计信息;确定各采集参数对应的事件名称,采用各事件名称和对应采集参数的业务统计信息生成应用的自定义事件报表。
上述自定事件的配置以及采集后统计生成报表的步骤具体如下:
参照图5,示出了根据本发明另一个实施例的自定义事件处理方法的步骤流程图。
步骤502,依据配置请求反馈业务管理页面。
步骤504,从业务管理页面中获取应用的应用路径,以及应用对应自定义事件的自定义事件信息。
步骤506,采用应用路径和自定义事件信息生成自定义管理信息。对移动终端中应用的一些特有事件进行自定义,以使通过自定义事件实现对应用中一些特有数据进行统计。首先依据配置请求,将应用对应的自定义事件进行处理反馈业务管理页面,并从业务管理页面中获取该应用对应的应用路径,如依据每条自定义事件确定其属于的哪条业务,再依据确定的业务信息,确定该业务对应的应用,依此,确定应用对应的应用路径,以及获取应用对应自定义事件的自定义事件信息,其中,自定义事件信息包括:事件名称和事件属性,自定义事件包括以下至少一种:流量统计事件、点击事件、选中事件。事件属性包括:自定义事件的统计方式。将应用路径、自定义事件的事件名称和事件属性生成自定义管理信息。如统计某一时间段内流量消耗情况,将流量统计事件设为自定义事件;并查找该段时间内所有应用有哪些在消耗流量;获取应用的对应的应用路径,现查找到该段时间内只有手机助手和浏览器在消耗流量,将手机助手和浏览器在该段时间内消耗流量的情况作为自定义管理信息。
步骤508,依据应用路径确定应用。
步骤510,针对应用,获取各自定义事件的事件名称和事件属性对应的业务统计信息。依据业务管理页面中的应用路径确定应用,从确定应用路径后的应用中获取对应每条自定义事件的事件名称和事件属性对应的业务统计信息。在进行业务统计之前可以配置各应用的采集参数以及采集配置信息,从而对采集参数进行采集并上传。在初始配置时可以配置各应用的采集参数以及采集配置信息,云服务器可以将采集参数和采集配置信息下发到应用所在终端。当应用所在终端通过采集工具对各应用进行数据采集时,采集工具如调用SDK(Software Development Kit,软件开发工具包)就可以对各应用进行数据采集,即依据采集配置信息采集应用中各采集参数的参数信息,其中采集参数包括静态参数和动态参数。在接收到上传的各参数信息之后,可以进行业务统计。其中,依据所述自定义管理信息获取业务统计信息,包括如下子步骤:针对每个自定义事件,获取事件名称对应的逻辑名称,以及事件属性对应的逻辑属性。查找逻辑名称对应采集参数,依据逻辑属性确定采集参数对应的业务统计信息。
服务器依据自定义管理信息进行数据处理和数据统计,在每条自定义事件中,都有对应的事件名称和对应的逻辑名称,如页面中的某按钮触发事件,首先对该页面的中按钮依次进行编号,再将按钮触发事件定义为按钮事件,如事件名称为按钮1,对应的逻辑名称为button。每条自定义事件都对应有逻辑属性,采用统计的方式对每条自定义事件进行统计,如某页面按钮触发事件定义为按钮事件1,在其触发一次,对其进行累加,取其最终值。依据每条自定义事件,获取每条自定义事件名称对应的逻辑名称,以及事件属性对应的逻辑属性,所谓的逻辑名称和逻辑属性实际为底层代码中自定义事件的一种表现形式,后台服务器以逻辑名称和逻辑属性对数据进行统计。每个应用对应一项业务,每项业务对应有多个条自定义事件,依据每条事件的逻辑名称查找该自定义事件对应的采集参数,依据逻 辑属性,对采集参数以统计的方式进行业务统计,得到该条自定义事件对应的业务统计信息;依此,确定出每条自定义事件对应的业务统计信息。如,某页面包括三段文字,现需统计其中每段,被选中且被复制的次数;将其定义为一项业务,再定义三种自定义事件,如第一段被选中且被复制的事件定义为选中1、第二段被选中且被复制的事件定义为选中2、第三段被选中且被复制的事件定义为选中3;自定义事件选中的逻辑名称为check;采集参数包括自定义事件选中的执行次数,即每段文字被选中且复制的次数。又如某时间段内,第一段文字被选中且复制的次数为0,第二段文字被选中且复制的次数为1,第三段文字被选中且复制的次数为6。相应的,事件名称为选中1、逻辑名称为check1、采集参数对应的业务统计信息为0;事件名称为选中2、逻辑名称为check2、采集参数对应的业务统计信息为1;事件名称为选中3、逻辑名称为check3、采集参数对应的业务统计信息为6。依据事件名称确定与之对应的逻辑名称,依据事件属性确定一致对应的逻辑属性;再依据逻辑名和逻辑属性,确定相应的采集参数和业务统计信息;可以清楚的确定每条自定义事件对应的业务统计信息。
步骤512,确定各采集参数对应的事件名称,采用各事件名称和对应采集参数的业务统计信息生成应用的自定义事件报表。数据分析服务器接收参数信息,并依据参数信息确定各个应用对应自定义事件的事件名称、逻辑名称、采集参数对应的业务统计信息;并将自定义事件的事件名称、逻辑名称、采集参数对应的业务统计信息发送给报表生成服务器;报表生成服务器依据每项业务确定出该业务对应的多条自定义事件,再依据该定义事件,确定该自定义事件对应的事件名称、逻辑名称、采集参数对应的业务统计信息;依据每条自定义事件对应的事件名称和采集参数对应的业务统计信息生成应用的自定义事件报表,其中业务统计信息即采集参数对应的采集数据,采集的数据以累加的方式进行统计。
步骤514,获取通用事件信息对应的业务统计信息,将通用事件对应业务统计信息添加到自定义事件报表中。本发明的一种可选实施例,对于通用事件只需依据通用事件对应的事件名称获取其对应的业务统计信息,将通用事件的事件名称以及通用事件对应的业务统计信息,添加到自定义事件报表中。本发明实施例通过从业务管理界面中获取应用的应用路径,以及应用对应自定义事件的自定义事件信息;依据应用路径确定应用,针对应用,获取各自定义事件的事件名称和事件属性对应的业务统计信息,依据业务统计信息生成自定义事件报表,每个应用对应一项业务,一项业务包括多条自定义事件,依据每条自定义事件对应的业务统计,生成自定义事件报表;在自定义事件报表中可以直观的表示出每条自定义事件对应的业务统计数据,这样的统计方式更加具有代表性,更能统计出一些特有事件,增强了统计效果;本发明实施例还可以将通用事件添加到自定义事件报表中,实现了通用事件和自定义事件的结合统计,使得用户可以从一个业务报表中获取所需的各种事件的统计信息,满足各种用户需求。其中,所述采集控制服务器,还用于配置所述目标应用对应测试设备的测试信息;所述数据分析服务器,还用于对所述目标应用对应上传的参数信息进行分析;判断所述参数信息属于测试设备时,实时对属于测试设备的参数信息进行分析;所述报表生成服务器,还用于判断所述参数信息属于测试设备时,依据数据分析结果实时生成数据报表。其中,所述采集控制服务器102,包括:开发配置服务器1024;所述开发配置服务器,用于在目标应用完成注册后,对所述目标应用配置至少一个测试设备的测试标识;为所述目标应用配置待测试的采集参数,将所述测试标识和采集参数作为测试信息;所述数据分析服务器,还用于从上传的参数信息中获取目标应用对应采集参数的参数信息;通过所述参数信息中终端参数对应终端标识;判断所述终端标识与测试设备表中测试标识是否相同,当所述终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备。所述的方法还包括:所述采集控制服务器配置所述目标应用对应测试设备的测试信息;所述数据分析服务器对所述目标应用对应上传的参数信息进行分析;判断所述参数信息属于测试设备时,实时对属于测试设备的参 数信息进行分析;所述报表生成服务器判断所述参数信息属于测试设备时,依据数据分析结果实时生成数据报表。配置所述目标应用对应测试设备的测试信息,包括:在目标应用完成注册后,对所述目标应用配置至少一个测试设备的测试标识;为所述目标应用配置待测试的采集参数,将所述测试标识和采集参数作为测试信息;所述的方法还包括:所述数据分析服务器从上传的参数信息中获取目标应用对应采集参数的参数信息;通过所述参数信息中终端参数对应终端标识;判断所述终端标识与测试设备表中测试标识是否相同,当所述终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备。
在开发配置服务器1024配置目标应用并进行测试的步骤具体如下:
参照图6,示出了根据本发明另一个实施例的目标应用的测试方法的步骤流程图。
步骤602,接收目标应用的注册请求。
步骤604,依据注册请求为目标应用分配应用标识。
为了应用的开发与维护,可以在应用运行过程中采集相应的采集参数来确定应用的运行情况,本实施例各应用采用通用的采集工具,因此可以预先测试应用调用采集工具进行参数采集是否正常,可以将需要测试的应用作为目标应用。目标应用的测试通常需要实时获知测试结果,因此可以为目标应用配置测试设备,实时对测试设备的采集结果进行分析。首先对目标应用进行注册,可以发出注册请求,该注册请求中携带有目标应用的相关信息,服务器中获取依据注册请求为目标应用分配应用标识,从而通过应用标识唯一标识一款应用程序。在目标应用完成注册后,可以发送采集工具即采集数据所需的SDK给目标应用,使得目标应用能够在运行时调用该采集工具进行采集。
步骤606,对目标应用,配置至少一个测试设备的测试标识。
步骤608,为目标应用配置待测试的采集参数,将测试标识和采集参数作为测试信息。目标应用完成注册后,可以上传测试设备的终端标识如M2值给开发配置服务器,开发配置服务器将终端标识配置为测试设备的测试标识,从而可以对目标应用配置至少一个测试设备的测试标识。还可以配置目标应用待测试的采集参数,即确定测试时需要从目标应用中采集的采集参数,从而得到相应采集参数的参数信息。将测试标识和采集参数作为测试信息。从而目标应用可以调用采集工具进行采集,即目标应用为添加采集工具的测试应用。云服务器依据采集参数以及相应的采集策略生成采集配置信息,将采集配置信息下发给各数据终端,使得各相应的应用可以依据采集配置信息对采集参数对应的参数信息进行上报,即云服务器可以通过采集参数和采集配置信息控制应用所在的终端采集各采集参数对应的参数信息,自动完成应用的数据采集。终端设备依据采集配置信息,调用采集工具,如调用SDK对目标应用进行参数的采集,并将采集的到的参数信息上传给数据分析服务器。
步骤610,从上传的参数信息中获取目标应用对应采集参数的参数信息。
步骤612,对参数信息的来源进行分析,判断参数信息是否属于测试设备。数据分析服务器从上传的参数信息中获取目标应用对应采集参数的参数信息,然后从参数信息中查找终端参数对应终端标识,将该终端标识和预先配置的测试设备表中测试标识进行比对,判断所述终端标识与测试设备表中测试标识是否相同,当所述终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备,即该参数信息是从测试设备中采集得到的。根据本发明一个可选实施例中,判断参数信息是否属于测试设备,具体可以包括:通过参数信息中终端参数对应终端标识,确定参数信息的来源;判断终端标识与测试设备表中测试标识是否相同;当终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备。本实施例中,可以在服务器中保存各测试设备的测试标识,生成相应的测试设备表,便于后续分析时确定测试设备。从参数信息中查找终端参数对应终端标识,该终端标识可以标识参数信息的来源,即是从哪个终端中采集得到的。将终端标识与测试设备表中的测试标识进行比对, 判断终端标识与测试设备表中测试标识是否相同,即判断当前参数信息是否属于测试设备。若是,即终端标识与测试设备表中任一测试标识相同,则判断参数信息属于测试设备,即该参数信息是从测试设备中采集得到的。反之,若终端标识与测试设备表中测试标识均不相同,则该参数信息不是从测试设备中采集得到的,即参数信息不属于测试设备,可以按照通用的处理流程进行统计生成报表,而无误实时统计。通过终端标识来确定上传的参数信息是否来自测试设备,若是,即参数信息属于测试设备,执行步骤614;若否,即参数信息不属于测试设备,结束该流程,无需实时统计。
步骤614,针对属于测试设备的各个参数信息,分别按照统计方式对相应参数信息进行统计。
步骤616,依据各参数信息对应统计结果生成测试报表。在确定参数信息属于测试设备后,对测试设备的各个参数信息进行处理,其中按照统计的方式对相应的参数信息进行统计。如某页面某个按钮触发的次数,对该页面的所有按钮进行编号,即每个按钮都有自己对应的编号,按钮触发一次,对按钮触发的次数进行叠加,如编号为1的按钮触发了3次,即对应统计的数据包括按钮1触发3次。又如页面的切换,首先确定当前页面信息,再向上查找,确定上一页面的页面信息,若当前页面为首页,则将上一页面记录为空,再查找下一页面的页面信息,依次进行统计。依据各参数对应的统计信息,确定每个目标应用对应的一个或多个采集参数;并确定每个参数对应的统计数据,按照应用的分类将各个参数和参数对应的统计数据生成测试报表。
步骤618、依据测试报表分析采集工具在目标应用中的运行结果。目标应用中添加有采集工具,从而通过采集工具辅助目标应用对测试信息的采集。在采集、上传并实时统计生成测试报表后,还可以依据测试报表分析采集工具在目标应用中的运行结果。运行结果包括以下至少一项:数据采集结果、数据上传结果、报表生成结果和应用运行结果。数据采集结果即通过测试报表分析测试设备中采集工具对参数的采集情况,如是否能够正常采集。数据上传结果即通过测试报表分析测试设备中采集工具的参数信息上传情况,如上传是否正常。报表生成结果即通过测试报表分析测试设备中采集工具上传参数信息后,报表生成情况,即能够正常统计参数信息生成报表。应用运行结果即通过测试报表分析测试设备通过采集工具进行采集、上传时目标应用的运行情况,如目标应用运行是否正常,是否出现卡顿、闪退、崩溃等问题。
本发明实施例通过在测试设备中安装目标应用,再为目标应用分配应用标识,为测试设备配置测试标识,将目标应用的采集参数和测试标识作为测试信息上传服务器,服务器通过解析多个设备上传的数据信息,依据测试标识确定测试信息所属的测试设备,对参数信息以统计方式进行统计,依据统计结果生成测试报表,通过测试报表能够清楚的反应当前目标应用在测试设备的运行情况;还可以在目标应用中安装采集工具的测试应用辅助参数信息的采集,利用测试报表分析采集工具在目标应用中的运行情况。所述数据分析服务器104,还用于从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果。所述数据分析服务器104,用于确定校验参数的参数标识,从所述参数信息中查找所述参数标识对应校验信息;检测所述校验信息是否为目标信息;若所述校验信息不为目标信息,确定流量存在劫持异常,在所述劫持校验结果中记录劫持异常;若所述校验信息为目标信息,确定数据传输正常,在所述劫持校验结果中记录传输正常。所述的方法还包括:数据分析服务器从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果。从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果,包括:确定校验参数的参数标识,从所述参数信息中查找所述参数标识对应校验信息;检测所述校验信息是否为目标信息;若所述校验信息不为目标信息,确定流量存在劫持异常,在所述劫持校验结果中记录劫持异常;若所述校验信息为目标信息,确定数据传输正常,在所述劫持校验结果中记录传输正常。
参数信息采集完成统计时,还可以检验传输以及统计结果,其中对于传输的校验步骤具体如下:
参照图7,示出了根据本发明另一个实施例的传输校验方法的步骤流程图。
步骤702,接收上传的参数信息。其中,所述参数信息为应用运行时针对各采集参数采集得到的。在数据采集分析系统中,采集控制服务器基于各服务平台所需要采集的数据,确定待采集的应用。在确定应用后,云服务器可以根据应用类型确定待采集的应用的静态参数、动态参数,以及设置采集配置信息,使得各应用或者应用的终端可以按照该采集配置信息采集、上传采集到的各采集参数对应参数信息。可选的,上传的参数信息可以包括:劫持后中转返回目的地址的参数信息,以及直接上传目的地址的参数信息。其中,目的地址属于地址列表。实质上,可以在数据分析服务器预先设置地址列表。该地址列表包含了上传到数据分析服务器的各IP地址,相当于目标地址;以及各IP地址对应的地址信息,相当于目标地址信息。当参数信息需要上传到某一目标地址,可以将该目标地址作为目的地址。在具体实现中,通过确定上传的IP地址,参数信息可以从应用所在终端上传到数据分析服务器。因此,可以在参数信息中记录其上传的IP地址,生成上传目的地址的参数信息,如记录上一次上传IP地址生成LastIP信息。其中,上传目的地址的参数信息可以包括直接上传目的地址的参数信息和劫持后中转返回目的地址的参数信息等。
步骤704,确定校验参数的参数标识,从所述参数信息中查找所述参数标识对应校验信息。在本发明实施例中,数据分析分析服务器可以根据校验需求,确定需要校验的校验参数。通过确定校验参数的参数标识,就可以依据所确定的参数标识进行查找。若从参数信息中查找到所确定的参数标识对应的校验信息,就可以将找到的校验信息提取出来,以便检测参数信息在传输过程中是否被拦截。作为本发明的一个具体示例,假设参数信息从终端A上传到数据分析服务器B中,分析服务器B在确定IP地址的标识符后,依据该IP地址的标识符就可以从上传的参数信息中提取IP地址的标识符对应的LastIP信息,该LastIP信息包含了参数信息从终端A到分析服务器B上传的各IP地址,如LastIP1、LastIP2、LastIP3等。
步骤706,检测所述校验信息是否为目标信息。若所述校验信息不为目标信息,则执行步骤708;若所述校验信息为目标信息,则执行步骤710。可选的,数据分析服务器可以通过检测IP地址信息与地址列表中的目标地址信息匹配,判断参数信息是否被拦截过。在本发明的一个优选实施例中,上述步骤706可以是检测所述IP地址信息与地址列表中的目标地址信息匹配。具体的,若从参数信息中所提取的IP地址信息对应的IP地址不在预置的地址列表中,即在地址列表不能查找到所提取的IP地址信息对应的目标地址时,判定所提取的IP地址信息与地址列表中的目标地址信息不匹配,则可以确定参数信息被拦截过,执行步骤708。若从参数信息中所提取的IP地址信息对应的IP地址在预置的列表中,即在地址列表可以查找到所提取的IP地址信息对应的IP地址,判定所提取的IP地址信息与地址列表中的目标地址信息匹配,则可以确定参数信息没有被拦截过,执行步骤710。结合上述例子,若能在预置的地址列表中查找到LastIP1、LastIP2以及LastIP3,则可以确定参数信息没有被拦截,执行步骤710;若不能在地址列表中查找到LastIP1,可以判断出参数信息被非法终端或恶意程序拦截,且拦截参数信息的非法终端或恶意程序对应的IP地址为LastIP1,则执行步骤708。
步骤708,确定流量存在劫持异常,在所述劫持校验结果中记录劫持异常。具体的,数据分析服务器确定参数信息被拦截过,就可以确定参数信息上传过程中存在流量劫持现象,并且此次接收到的参数信息有可能被拦截的终端或恶意程序篡改,即可以确定该参数信息上传所对应的流量存在劫持异常,在劫持校验结果中记录该参数信息的劫持异常,如在劫持校验结果中记录参数信息被LastIP1的终端拦截或者记录LastIP1为非法IP地址、恶意IP地址等,生成数据分析结果,从而可以避免采用被拦截的参数信息进行统计,保证数据分析结果的准确性。
步骤710,确定数据传输正常,在所述劫持校验结果中记录传输正常。当参数信息没有拦截过,就可以确定数据传输正常,劫持校验结果中记录该参数信息传输正常,保证了数据分析结果的准确性。
所述数据分析服务器104,还用于从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果。所述数据分析服务器104,用于确定存储参数的存储标识,从所述参数信息中查找所述存储标识对应存储信息;依据所述存储信息查找至少一个终端标识;当所述存储信息对应一个终端标识,生成质量合格的质量校验结果;当所述存储信息对应多于一个终端标识,查找所述终端标识对应成功上传信息;将各终端标识对应上传成功信息进行排序,依据排序结果确定所述上传成功信息不存在冗余时,判断数据异常,生成数据异常的质量校验结果。
实际上,当数据终端(简称终端)如手机、平板电脑通过采集工具采集到应用数据后,即在采集到各采集参数对应的参数信息后,就会将采集到的参数信息上传,使得数据分析服务器可以接收到该上传的参数信息。该参数信息可以包括存储信息、校验信息和采集参数对应的信息等。其中,存储信可以用来检测数据质量,确定质量校验结果,如安全数码卡(Secure Digital Memory Card)信息(简称SD卡信息)、多媒体存储卡(Multi Media Card,MMC)信息、SM卡(Smart Media Card)信息、CF卡(Compact Flash Card)信息等;校验信息可以用于分析数据传输情况,确定劫持校验结果,如IP(Internet Protocol)地址信息。在接收到参数信息后,数据分析服务器可以对参数信息进行分析,从所述参数信息中查找存储参数对应存储信息。具体的,可以根据检测需要设预置存储参数,如预置SD卡参数。在数据分析的过程中,通过查找预置的存储参数对应的存储信息,就可以获取到该存储参数所对应的存储信息。数据分析服务器在提取到存储信息后,采用存储信息对参数信息进行数据质量检测,以判断采集到的参数信息是否存在数据造假,即判断采集到的参数信息的准确性,确定质量校验结果。所述的方法还包括:所述数据分析服务器从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果。从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果,包括:确定存储参数的存储标识,从所述参数信息中查找所述存储标识对应存储信息;依据所述存储信息查找至少一个终端标识;当所述存储信息对应一个终端标识,生成质量合格的质量校验结果;当所述存储信息对应多于一个终端标识,查找所述终端标识对应成功上传信息;将各终端标识对应上传成功信息进行排序,依据排序结果确定所述上传成功信息不存在冗余时,判断数据异常,生成数据异常的质量校验结果。
参数信息采集完成后,还可以检验所采集数据的质量,其中对于传输的数据的质量校验步骤具体如下:
参照图8,示出了根据本发明另一个实施例的数据质量校验方法的步骤流程图。
步骤802,接收上传的参数信息。其中,所述参数信息为应用运行时针对各采集参数采集得到的。在数据采集分析系统中,采集控制服务器基于各服务平台所需要采集的数据,确定待采集的应用。在确定应用后,云服务器可以根据应用类型确定待采集的应用的静态参数、动态参数,以及设置采集配置信息,使得各应用或者应用的终端可以按照该采集配置信息采集、上传采集到的各采集参数对应参数信息。
步骤804,确定存储参数的存储标识,从所述参数信息中查找所述存储标识对应存储信息。在本发明实施例中,数据分析分析服务器可以根据数据质量检测的需求,确定所需要提取的存储信息,采用所提取的存储信息对参数信息进行数据质量检测,以判断上传的参数信息是否异常。具体的,通过确定存储参数的存储标识,就可以依据所确定的参数标识进行查找;若从参数信息中查找到所确定的存储标识对应存储信息,就可以将找到的存储信息提取出来,以便对上传的参数信息进行数据质量的检测,如判断上传的参数信息是否为造假的数据。实际上,数据分析服务器设置的存储参数可以包括 SD卡参数,则存储参数对应存储信息可以包括SD卡信息。作为本发明的一个具体示例,数据分析服务器可以通过确定SD卡标识符,就可以依据SD卡标识符对接收到的参数信息进行查找,从参数信息中提取该SD卡标识符对应SD卡信息。需要说明的是,每个SD卡具有唯一对应的SD卡标识,并且SD卡信息可以用于查找SD卡所对应的SD卡标识。
步骤806,依据所述存储信息查找至少一个终端标识。在提取存储信息后,就可以依据存储信息进行数据质量检测,判断采集到的参数信息是否存在数据造假。具体的,从接收到的所有参数信息中提取各终端的标识信息;并判断所提取标识信息的终端标识是否对应所提取的存储信息;若是终端标识是否对应所提取的存储信息,即可以确定所提取的存储信息为该终端的存储信息,建立所提取存储信息与该终端的终端标识的对应关系。作为本发明的一个具体示例,假设终端A、终端B以及终端C连接同一个SD卡,标注为SD卡1,并且将SD卡1的SD卡信息标注为SD卡信息1;终端D连接另一个SD卡,标注为SD卡2,并且将SD卡2的SD卡信息标注为SD卡信息2。当数据分析服务器从终端A、终端B或终端C上传的参数信息中提取SD卡信息时,其所提取的SD卡信息为SD卡信息1,依据SD卡信息1查找SD卡标识,可以找到终端A对应的SD卡标识、终端B对应的SD卡标识以及终端C对应的SD卡标识,即依据SD卡信息1查找上传的参数信息,可以得到SD卡信息1所对应的3个SD卡标识。当数据分析服务器从终端D上传的参数信息中提取SD卡信息时,其所提取的SD卡信息为SD卡信息2,依据SD卡信息2查找SD卡标识,可以找到终端D对应的SD卡标识,即依据SD卡信息2查找上传的参数信息,可以得到SD卡信息2所对应的1个SD卡标识。
步骤808,采用所述终端标识检测数据质量,确定质量校验结果。在具体实现中,数据分析服务器可以对存储信息所对应的终端标识进行统计,确定该存储信息对应终端标识的数量,基于终端标识的数量判断该存储信息是否属于一个终端,相当于判断该存储信息所对应的参数信息是否存在数据造假。若存储信息对应的终端标识的数量为1,则该存储信息属于一个终端,如上述例子中,SD卡信息2属于终端D,可以判定采集到的数据正常,即确定SD卡信息2所对应的参数信息不是造假的数据,生成该数据采集质量合格的质量校验结果。若存储信息对应的终端标识的数量不为1,则该存储信息不是属于一个终端,如上述例子中,SD卡信息1属于3个终端,可以判定采集到的数据异常,即SD卡信息1所对应的参数信息可能是造假的数据,生成该数据异常的质量校验结果。可选的,当所述存储信息对应一个终端标识,生成质量合格的质量校验结果。当所述存储信息对应多于一个终端标识,生成数据异常的质量校验结果。具体的,当存储信息对应一个终端标识时,数据分析服务器可以判断该存储信息所对应的参数信息为正常数据,可以采用该参数信息进行数据分析,生成各服务平台所需要的数据报表,以了解业务需求,对业务进行调整。可选的,当所述终端标识存在多于一个终端标识时,查找所述终端标识对应成功上传信息;将各终端标识对应上传成功信息进行排序;依据排序结果确定所述上传成功信息不存在冗余时,判断数据异常。实际上,一些应用所在的终端设备如显示器,在本地没有存储空间,通过连接处理器或者硬盘,利用处理器或者硬盘的存储空间处理数据。其中,多个终端可以共用同一个处理器或者硬盘的存储空间处理数据,如多个显示器连接同一个SD卡,即共用同一个SD卡的存储空间。在采集数据过程中,对连接同一个硬盘或者处理器的多个终端进行数据采集,实质上采集到的参数信息是同一个硬盘或者处理器的数据。当存储信息对应多于一个终端标识时,数据分析服务器可以查找各终端标识对应成功上传信息,如成功传输日志信息(transformation)。终端标识对应成功上传信息包括了成功传输次数,如成功传输日志的次数transformation times(简称为tt值)。每一次成功上传采集到的参数信息,tt值自动按照单位值增加,如自动加1。在存储信息对应终端标识多于一个时,数据分析服务器可以将各终端标识对应上传成功信息进行排序,如按照tt值的大小进行排序,基于排序结果判断上传成功信息是否存在冗余。当上传 成功信息不存在冗余时,可以确定存储信息对应的多个终端标识实质上是同一个处理器或者硬盘的数据,即存在数据造假,判定数据异常。结合上述例子,SD卡信息1对应3个SD卡标识,数据分析服务器按照tt值的大小,对成功传输日志的次数进行排序,判断成功传输日志的次数是否重复;当成功传输日志的次数不重复时,即在成功传输日志的次数不存在冗余时,可以判定数据异常,如假设终端A对应的SD卡标识的tt值为1,终端B对应的SD卡标识的tt值为3,终端C对应的SD卡标识的tt值为2,即成功传输日志的次数不存在冗余,可以判定包含SD卡信息1的参数信息异常,相当于确定包含SD卡信息1的参数信息存在数据造假,生成数据异常的质量校验结果,避免该参数信息进行数据分析,即避免采用异常的参数信息进行分析,提高数据采集的准确度。在本发明实施例中,当存储信息对应多于一个终端标识时,数据分析服务器可以判定数据异常,生成数据异常的质量校验结果,以避免采用异常的数据进行数据分析,保证数据分析结果的准确性。
对于方法实施例,为了简单描述,故将其都表述为一系列的动作组合,但是本领域技术人员应该知悉,本发明实施例并不受所描述的动作顺序的限制,因为依据本发明实施例,某些步骤可以采用其他顺序或者同时进行。其次,本领域技术人员也应该知悉,说明书中所描述的实施例均属于优选实施例,所涉及的动作并不一定是本发明实施例所必须的。对于装置实施例而言,由于其与方法实施例基本相似,所以描述的比较简单,相关之处参见方法实施例的部分说明即可。在此提供的算法和显示不与任何特定计算机、虚拟系统或者其它设备固有相关。各种通用系统也可以与基于在此的示教一起使用。根据上面的描述,构造这类系统所要求的结构是显而易见的。此外,本发明也不针对任何特定编程语言。应当明白,可以利用各种编程语言实现在此描述的本发明的内容,并且上面对特定语言所做的描述是为了披露本发明的最佳实施方式。在此处所提供的说明书中,说明了大量具体细节。然而,能够理解,本发明的实施例可以在没有这些具体细节的情况下实践。在一些实例中,并未详细示出公知的方法、结构和技术,以便不模糊对本说明书的理解。类似地,应当理解,为了精简本公开并帮助理解各个发明方面中的一个或多个,在上面对本发明的示例性实施例的描述中,本发明的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而,并不应将该公开的方法解释成反映如下意图:即所要求保护的本发明要求比在每个权利要求中所明确记载的特征更多的特征。更确切地说,如下面的权利要求书所反映的那样,发明方面在于少于前面公开的单个实施例的所有特征。因此,遵循具体实施方式的权利要求书由此明确地并入该具体实施方式,其中每个权利要求本身都作为本发明的单独实施例。本领域那些技术人员可以理解,可以对实施例中的设备中的模块进行自适应性地改变并且把它们设置在与该实施例不同的一个或多个设备中。可以把实施例中的模块或单元或组件组合成一个模块或单元或组件,以及此外可以把它们分成多个子模块或子单元或子组件。除了这样的特征和/或过程或者单元中的至少一些是相互排斥之外,可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述,本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。此外,本领域的技术人员能够理解,尽管在此所述的一些实施例包括其它实施例中所包括的某些特征而不是其它特征,但是不同实施例的特征的组合意味着处于本发明的范围之内并且形成不同的实施例。例如,在下面的权利要求书中,所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本发明的各个部件实施例可以以硬件实现,或者以在一个或者多个处理器上运行的软件模块实现,或者以它们的组合实现。本领域的技术人员应当理解,可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本发明实施例的数据采集分析系统中的一些或者全部部件的一些或者全部功能。本发明还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如, 计算机程序和计算机程序产品)。这样的实现本发明的程序可以存储在计算机可读介质上,或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到,或者在载体信号上提供,或者以任何其他形式提供。例如,图9示出了可以实现根据本发明的数据采集分析方法的计算设备。该计算设备传统上包括处理器910和以存储器920形式的程序产品或者可读介质。存储器920可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM或者ROM之类的电子存储器。存储器920具有用于执行上述方法中的任何方法步骤的程序代码931的存储空间930。例如,用于程序代码的存储空间930可以包括分别用于实现上面的方法中的各种步骤的各个程序代码931。这些程序代码可以从一个或者多个程序产品中读出或者写入到这一个或者多个程序产品中。这些程序产品包括诸如存储卡之类的程序代码载体。这样的程序产品通常为如参考图10所述的便携式或者固定存储单元。该存储单元可以具有与图9的计算设备中的存储器920类似布置的存储段、存储空间等。程序代码可以例如以适当形式进行压缩。通常,存储单元包括可读代码931’,即可以由例如诸如910之类的处理器读取的代码,这些代码当由计算设备运行时,导致该计算设备执行上面所描述的方法中的各个步骤。
应该注意的是上述实施例对本发明进行说明而不是对本发明进行限制,并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。在权利要求中,不应将位于括号之间的任何参考符号构造成对权利要求的限制。单词“包含”不排除存在未列在权利要求中的元件或步骤。位于元件之前的单词“一”或“一个”不排除存在多个这样的元件。本发明可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中,这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。本领域普通技术人员可以理解实现上述实施例方法中的全部或部分步骤可以通过程序来指令相关的硬件来完成,该程序可以存储于一计算机可读取存储介质中,比如ROM/RAM、磁碟、光盘等。以上所述的具体实施例,对本发明的目的、技术方案和有益效果进行了进一步详细说明,所应理解的是,以上所述仅为本发明的具体实施例而已,并不用于限定本发明的保护范围,凡在本发明的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。

Claims (32)

  1. 一种数据采集分析系统,包括:采集控制服务器、数据分析服务器、报表生成服务器和至少一个数据终端,所述数据终端中安装有采集工具;
    所述采集控制服务器,用于配置采集配置信息给数据终端并下发给相应的数据终端,其中,所述采集配置信息用于控制采集参数的采集;
    所述数据终端,用于在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集;以及将采集的参数信息上传给所述数据分析服务器;
    所述数据分析服务器,用于对上传的各采集参数对应参数信息进行分析,获取数据分析结果;将所述数据分析结果发送给所述报表生成服务器;
    所述报表生成服务器,用于依据所述数据分析结果生成数据报表。
  2. 根据权利要求1所述的系统,其特征在于,所述采集控制服务器包括云控服务器;
    所述云控服务器,用于依据应用类型确定所述应用的采集参数,其中,所述采集参数包括:动态参数和/或静态参数;依据所述应用和应用所在终端配置采集配置信息,其中,所述采集配置信息用于控制所述采集参数的采集和上传;将采集参数和采集配置信息下发给应用所在的数据终端。
  3. 根据权利要求2所述的系统,其特征在于,所述云控服务器,用于配置参数信息的上传条件和/或采样条件,将上传条件和/或采样条件添加到采集配置信息中;配置所述应用所在终端对应内存的采集阈值,将所述采集阈值添加到采集配置信息中;配置所述应用所在终端对应网络类型的上传间隔,将所述上传间隔添加到所述采集配置信息中;配置所述应用所在终端对应缓存阈值,将所述缓存阈值添加到采集配置信息中;以及,在所述采集配置信息中配置协议上传顺序、采样率和采样参数的优先级。
  4. 根据权利要求2所述的系统,其特征在于,所述数据终端,用于采用采集工具依据采集配置信息采集所述应用的静态参数的参数信息;以及,采用所述采集工具依据采集配置信息确定待采集的动态参数,依据所述应用的运行实时采集所述动态参数的参数信息。
  5. 根据权利要求4所述的系统,其特征在于,所述数据终端,用于当检测到所述应用的界面切换时,记录切换前的界面为上一页,记录切换后的界面为当前页,将所述上一页和当前页添加到应用界面启动信息中;当检测到所述应用的按钮被触发时,获取所述按钮对应的按钮编号,更新所述按钮编号对应的点击次数,将所述按钮编号和点击次数添加到按钮点击信息中;采集所述应用相关的运行时间作为时长信息,其中,所述时长信息包括:界面运行时间和应用运行时间。
  6. 根据权利要求2至5任一所述的系统,其特征在于,所述静态参数的参数信息包括以下至少一项:终端标识、版本信息、渠道信息、网络类型和分辨率信息;所述动态参数的参数信息包括以下至少一项:应用界面启动信息、按钮点击信息、时长信息、异常信息和会话信息。
  7. 根据权利要求1所述的系统,其特征在于,所述报表生成服务器,用于依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表。
  8. 根据权利要求7所述的系统,其特征在于,所述报表生成服务器,还用于从所述业务管理页面中获取所述应用的应用路径,以及所述应用对应自定义事件的自定义事件信息,其中,所述自定义事件信息包括:事件名称和事件属性;采用所述应用路径和自定义事件信息生成自定义管理信息。
  9. 根据权利要求8所述的系统,其特征在于,所述报表生成服务器,用于依据所述应用路径确定应用;针对每个自定义事件,获取所述事件名称对应的逻辑名称,以及所述事件属性对应的逻辑属性;查找所述逻辑名称对应采集参数,依据所述逻辑属性确定所述采集参数对应的业务统计信息;以及确定各采集参数对应的事件名称,采用各事件名称和对应采集参数的业务统计信息生成应用的自定 义事件报表。
  10. 根据权利要求1所述的系统,其特征在于,
    所述采集控制服务器,还用于配置所述目标应用对应测试设备的测试信息;
    所述数据分析服务器,还用于对所述目标应用对应上传的参数信息进行分析;判断所述参数信息属于测试设备时,实时对属于测试设备的参数信息进行分析;
    所述报表生成服务器,还用于判断所述参数信息属于测试设备时,依据数据分析结果实时生成数据报表。
  11. 根据权利要求10所述的系统,其特征在于,所述采集控制服务器,包括:开发配置服务器;
    所述开发配置服务器,用于在目标应用完成注册后,对所述目标应用配置至少一个测试设备的测试标识;为所述目标应用配置待测试的采集参数,将所述测试标识和采集参数作为测试信息;
    所述数据分析服务器,还用于从上传的参数信息中获取目标应用对应采集参数的参数信息;通过所述参数信息中终端参数对应终端标识;判断所述终端标识与测试设备表中测试标识是否相同,当所述终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备。
  12. 根据权利要求1所述的系统,其特征在于,所述数据分析服务器,还用于从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果。
  13. 根据权利要求12所述的系统,其特征在于,所述数据分析服务器,用于确定校验参数的参数标识,从所述参数信息中查找所述参数标识对应校验信息;检测所述校验信息是否为目标信息;若所述校验信息不为目标信息,确定流量存在劫持异常,在所述劫持校验结果中记录劫持异常;若所述校验信息为目标信息,确定数据传输正常,在所述劫持校验结果中记录传输正常。
  14. 根据权利要求1所述的系统,其特征在于,所述数据分析服务器,还用于从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果。
  15. 根据权利要求14所述的系统,其特征在于,所述数据分析服务器,用于确定存储参数的存储标识,从所述参数信息中查找所述存储标识对应存储信息;依据所述存储信息查找至少一个终端标识;当所述存储信息对应一个终端标识,生成质量合格的质量校验结果;当所述存储信息对应多于一个终端标识,查找所述终端标识对应成功上传信息;将各终端标识对应上传成功信息进行排序,依据排序结果确定所述上传成功信息不存在冗余时,判断数据异常,生成数据异常的质量校验结果。
  16. 一种数据采集分析方法,其中,所述数据采集分析方法应用于数据采集分析系统中,数据采集分析系统包括:所述采集控制服务器、数据分析服务器、报表生成服务器和至少一个数据终端,所述数据终端中安装有采集工具;
    所述的方法包括:所述采集控制服务器配置采集配置信息给数据终端并下发给相应的数据终端;所述数据终端在应用运行时调用所述采集工具,依据采集配置信息对采集参数的参数信息进行采集;所述数据终端将采集的参数信息上传给所述采集控制服务器;所述数据分析服务器对上传的各采集参数对应参数信息进行分析,获取数据分析结果;所述数据分析服务器将所述数据分析结果发送给所述报表生成服务器;所述报表生成服务器依据所述数据分析结果生成数据报表。
  17. 根据权利要求16所述的方法,其特征在于,所述采集控制服务器配置采集配置信息给数据终端并下发给相应的数据终端,包括:所述采集控制服务器依据应用类型确定所述应用的采集参数,其中,所述采集参数包括:动态参数和/或静态参数;依据所述应用和应用所在终端配置的采集配置信息,其中,所述采集配置信息用于控制所述采集参数的采集和上传;将采集参数和采集配置信息下发给应用所在的数据终端。
  18. 根据权利要求17所述的方法,其特征在于,依据所述应用和应用所在终端配置的采集配置信息的步骤包括以下至少一种:
    配置参数信息的上传条件和/或采样条件,将上传条件和/或采样条件添加到采集配置信息中;
    配置所述应用所在终端对应内存的采集阈值,将所述采集阈值添加到采集配置信息中;
    配置所述应用所在终端对应网络类型的上传间隔,将所述上传间隔添加到所述采集配置信息中;
    配置所述应用所在终端对应缓存阈值,将所述缓存阈值添加到采集配置信息中;
    在所述采集配置信息中配置协议上传顺序、采样率和采样参数的优先级。
  19. 根据权利要求17所述的方法,其特征在于,所述依据采集配置信息对采集参数的参数信息进行采集,包括:采用所述采集工具依据采集配置信息采集所述应用的静态参数的参数信息;采用所述采集工具依据采集配置信息确定待采集的动态参数,依据所述应用的运行实时采集所述动态参数的参数信息。
  20. 根据权利要求19所述的方法,其特征在于,依据所述应用的运行实时采集所述动态参数的参数信息的步骤包括以下至少一种:
    当检测到所述应用的界面切换时,记录切换前的界面为上一页,记录切换后的界面为当前页,将所述上一页和当前页添加到应用界面启动信息中;
    当检测到所述应用的按钮被触发时,获取所述按钮对应的按钮编号,更新所述按钮编号对应的点击次数,将所述按钮编号和点击次数添加到按钮点击信息中;
    采集所述应用相关的运行时间作为时长信息,其中,所述时长信息包括:界面运行时间和应用运行时间。
  21. 根据权利要求17至20任一所述的方法,其特征在于,所述静态参数的参数信息包括以下至少一项:终端标识、版本信息、渠道信息、网络类型和分辨率信息;所述动态参数的参数信息包括以下至少一项:应用界面启动信息、按钮点击信息、时长信息、异常信息和会话信息。
  22. 根据权利要求16所述的方法,其特征在于,所述报表生成服务器依据所述数据分析结果生成数据报表,包括:所述报表生成服务器依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表。
  23. 根据权利要求22所述的方法,其特征在于,还包括配置自定义管理信息的步骤:
    从所述业务管理页面中获取所述应用的应用路径,以及所述应用对应自定义事件的自定义事件信息,其中,所述自定义事件信息包括:事件名称和事件属性;
    采用所述应用路径和自定义事件信息生成自定义管理信息。
  24. 根据权利要求23所述的方法,其特征在于,依据配置的应用对应自定义事件的自定义管理信息,获取业务统计信息;依据所述自定义管理信息和业务统计信息生成自定义事件报表,包括:依据所述应用路径确定应用;针对每个自定义事件,获取所述事件名称对应的逻辑名称,以及所述事件属性对应的逻辑属性;查找所述逻辑名称对应采集参数,依据所述逻辑属性确定所述采集参数对应的业务统计信息;确定各采集参数对应的事件名称,采用各事件名称和对应采集参数的业务统计信息生成应用的自定义事件报表。
  25. 根据权利要求16所述的方法,其特征在于,还包括:所述采集控制服务器配置所述目标应用对应测试设备的测试信息;所述数据分析服务器对所述目标应用对应上传的参数信息进行分析;判断所述参数信息属于测试设备时,实时对属于测试设备的参数信息进行分析;所述报表生成服务器判断所述参数信息属于测试设备时,依据数据分析结果实时生成数据报表。
  26. 根据权利要求25所述的方法,其特征在于,配置所述目标应用对应测试设备的测试信息, 包括:在目标应用完成注册后,对所述目标应用配置至少一个测试设备的测试标识;为所述目标应用配置待测试的采集参数,将所述测试标识和采集参数作为测试信息;
    所述的方法,其特征在于,还包括:所述数据分析服务器从上传的参数信息中获取目标应用对应采集参数的参数信息;通过所述参数信息中终端参数对应终端标识;判断所述终端标识与测试设备表中测试标识是否相同,当所述终端标识与测试设备表中任一测试标识相同时,判断参数信息属于测试设备。
  27. 根据权利要求16所述的方法,其特征在于,还包括:数据分析服务器从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果。
  28. 根据权利要求27所述的方法,其特征在于,从所述参数信息中查找校验参数对应校验信息;对所述校验信息进行分析确定劫持校验结果,包括:确定校验参数的参数标识,从所述参数信息中查找所述参数标识对应校验信息;检测所述校验信息是否为目标信息;若所述校验信息不为目标信息,确定流量存在劫持异常,在所述劫持校验结果中记录劫持异常;若所述校验信息为目标信息,确定数据传输正常,在所述劫持校验结果中记录传输正常。
  29. 根据权利要求16所述的方法,其特征在于,其特征在于,还包括:所述数据分析服务器从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果。
  30. 根据权利要求29所述的方法,其特征在于,其特征在于,从所述参数信息中查找存储参数对应存储信息;依据所述存储信息检测数据质量,确定质量校验结果,包括:确定存储参数的存储标识,从所述参数信息中查找所述存储标识对应存储信息;依据所述存储信息查找至少一个终端标识;
    当所述存储信息对应一个终端标识,生成质量合格的质量校验结果;当所述存储信息对应多于一个终端标识,查找所述终端标识对应成功上传信息;将各终端标识对应上传成功信息进行排序,依据排序结果确定所述上传成功信息不存在冗余时,判断数据异常,生成数据异常的质量校验结果。
  31. 一种程序,包括可读代码,当所述可读代码在计算设备上运行时,导致所述计算设备执行根据权利要求16-30中的任一个所述的数据采集分析方法。
  32. 一种可读介质,其中存储了如权利要求31所述的程序。
PCT/CN2016/104923 2015-12-15 2016-11-07 一种数据采集分析系统和方法 Ceased WO2017101606A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201510938627.6A CN105553769B (zh) 2015-12-15 2015-12-15 一种数据采集分析系统和方法
CN201510938627.6 2015-12-15

Publications (1)

Publication Number Publication Date
WO2017101606A1 true WO2017101606A1 (zh) 2017-06-22

Family

ID=55832708

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/104923 Ceased WO2017101606A1 (zh) 2015-12-15 2016-11-07 一种数据采集分析系统和方法

Country Status (2)

Country Link
CN (1) CN105553769B (zh)
WO (1) WO2017101606A1 (zh)

Cited By (38)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109905253A (zh) * 2017-12-07 2019-06-18 航天信息股份有限公司 一种日志信息采集方法及装置
CN110159252A (zh) * 2019-06-04 2019-08-23 国网北京市电力公司 数据采集系统及方法
CN110633205A (zh) * 2019-06-20 2019-12-31 北京无限光场科技有限公司 一种埋点事件的检测方法、装置、终端设备及介质
CN110995524A (zh) * 2019-10-28 2020-04-10 北京三快在线科技有限公司 流量数据监控方法、装置、电子设备和计算机可读介质
CN111198942A (zh) * 2018-10-31 2020-05-26 合肥神策数据网络科技有限公司 数据分析报告生成方法、装置、移动终端及存储介质
CN111611256A (zh) * 2020-04-30 2020-09-01 广东良实机电工程有限公司 设备能耗监测方法、装置、终端设备及存储介质
CN112015870A (zh) * 2020-09-14 2020-12-01 支付宝(杭州)信息技术有限公司 数据上传方法及装置
CN112130854A (zh) * 2020-09-09 2020-12-25 海看网络科技(山东)股份有限公司 一种iptv检测探针系统关键字的方法
CN112181804A (zh) * 2020-08-31 2021-01-05 五八到家有限公司 一种参数校验方法、设备以及存储介质
CN112328619A (zh) * 2020-09-24 2021-02-05 杭州小电科技股份有限公司 数据质量监控方法、装置、系统、电子装置和存储介质
CN112395173A (zh) * 2019-08-14 2021-02-23 腾讯科技(深圳)有限公司 信息流数据上报的方法和装置
CN112434023A (zh) * 2019-08-26 2021-03-02 长鑫存储技术有限公司 工艺数据分析方法及装置、存储介质及计算机设备
CN112817782A (zh) * 2021-02-20 2021-05-18 腾讯科技(深圳)有限公司 一种数据采集上报方法、装置、电子设备和存储介质
CN113014647A (zh) * 2021-02-25 2021-06-22 浙江正元智慧科技股份有限公司 一种基于大数据的运维平台远程数据采集系统
CN113114736A (zh) * 2021-03-25 2021-07-13 北京数字磐石科技有限公司 矿机管理方法和系统
CN113126562A (zh) * 2020-01-16 2021-07-16 智能云科信息科技有限公司 数据采集方法、装置、系统及计算机可读存储介质
CN113515507A (zh) * 2021-03-12 2021-10-19 中电建电力检修工程有限公司 应用于大坝渗水检测的方法及系统
CN113626477A (zh) * 2021-07-19 2021-11-09 浙江浙大中控信息技术有限公司 基于水厂物联网系统的可配置报表系统及方法
CN113760564A (zh) * 2020-10-20 2021-12-07 北京沃东天骏信息技术有限公司 数据处理方法、装置和系统
CN114296009A (zh) * 2022-03-10 2022-04-08 山东汇能电气有限公司 一种变压器运行智能分析系统
CN114385478A (zh) * 2020-10-22 2022-04-22 腾讯科技(深圳)有限公司 一种数据采集上报方法、装置、电子设备和存储介质
CN114401289A (zh) * 2021-12-31 2022-04-26 深圳市麦谷科技有限公司 任务分批上传方法及系统
CN114460400A (zh) * 2022-01-19 2022-05-10 西北核技术研究所 一种脉冲电流注入自动化实验系统及方法
CN114615291A (zh) * 2021-12-08 2022-06-10 江苏众亿国链大数据科技有限公司 一种基于物联网的数据采集方法
CN114785784A (zh) * 2022-04-14 2022-07-22 中国第一汽车股份有限公司 数据处理方法、装置、电子设备
CN114827774A (zh) * 2022-04-26 2022-07-29 浙江正泰物联技术有限公司 一种电气数据采集方法、装置及系统
CN115004667A (zh) * 2020-04-24 2022-09-02 深圳市欢太科技有限公司 信息推送方法、装置、电子设备及计算机可读介质
CN115102936A (zh) * 2022-06-22 2022-09-23 苏州达家迎信息技术有限公司 批量信息上传方法、装置、存储介质及电子设备
CN115378722A (zh) * 2022-08-25 2022-11-22 山东中创软件商用中间件股份有限公司 跨网络安全域的动态数据上报方法、装置、设备及介质
CN115453052A (zh) * 2022-08-31 2022-12-09 安徽天维仪表有限公司 一种用于校定气体检测仪的数据自动采集系统
CN116303689A (zh) * 2023-05-25 2023-06-23 武汉科迪智能环境股份有限公司 数据报表的生成方法、装置、计算机设备及可读存储介质
CN117215542A (zh) * 2023-11-07 2023-12-12 上海华创自动化工程股份有限公司 一种自定义数据处理系统及方法
CN117724884A (zh) * 2023-11-20 2024-03-19 福建新大陆支付技术有限公司 一种基于数据分析的自动化测试方法
CN118474575A (zh) * 2024-07-12 2024-08-09 北京博维亚讯技术有限公司 一种集中器的数据采集分析方法及系统
CN118627524A (zh) * 2024-07-11 2024-09-10 宁波瑞辉智能科技有限公司 基于串口屏交互连网的poe数字化采集终端及其工作方法
CN118710129A (zh) * 2024-07-11 2024-09-27 广州中车轨道交通装备有限公司 一种交通装备生产质量信息管理方法及系统
CN119728817A (zh) * 2025-03-03 2025-03-28 浙江省北大信息技术高等研究院 一种终端设备数据传输方法、系统、设备和存储介质
CN121441902A (zh) * 2025-12-30 2026-01-30 天津七一二移动通信股份有限公司 一种cir自动化数据下载系统及方法

Families Citing this family (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105553769B (zh) * 2015-12-15 2019-03-05 北京奇虎科技有限公司 一种数据采集分析系统和方法
CN106101175B (zh) * 2016-05-25 2019-08-23 腾讯科技(深圳)有限公司 设备管控方法、装置和系统
CN107809344B (zh) * 2016-09-09 2021-01-22 中华电信股份有限公司 实时讯务量搜集与分析系统及方法
CN106549830A (zh) * 2016-11-09 2017-03-29 上海最会保网络科技有限公司 一种移动应用数据采集装置和方法
CN106506851B (zh) * 2016-11-28 2021-01-01 深圳前海谷谷力生物科技有限公司 移动终端的数据统计适配方法与装置
CN106649240A (zh) * 2016-12-27 2017-05-10 北京奇虎科技有限公司 基于自定义事件展示报表的方法及装置
CN106649241A (zh) * 2016-12-27 2017-05-10 北京奇虎科技有限公司 基于自定义事件生成报表的方法及装置
CN107102860A (zh) * 2017-04-21 2017-08-29 上海青橙实业有限公司 数据采集方法、移动终端以及服务器
CN107018046A (zh) * 2017-06-06 2017-08-04 上海鋆创信息技术有限公司 一种数据采集方法、装置、终端及存储介质
CN109769305A (zh) * 2017-11-09 2019-05-17 普天信息技术有限公司 调度处理的方法、基站、电子设备和存储介质
CN108418787B (zh) * 2018-01-02 2021-02-26 深圳壹账通智能科技有限公司 企业资源计划数据的采集方法、终端设备及介质
CN110221922A (zh) * 2018-03-02 2019-09-10 网易(杭州)网络有限公司 程序产品的卡顿定位方法及装置、介质及计算设备
CN108833459B (zh) * 2018-04-09 2022-05-13 平安普惠企业管理有限公司 数据上报方法及终端设备
CN110391925A (zh) * 2018-04-20 2019-10-29 阿里巴巴集团控股有限公司 一种数据采集方法、数据采集装置及服务器
CN108762960B (zh) * 2018-05-14 2021-07-06 国网福建省电力有限公司 一种移动应用监测系统
CN109189664B (zh) * 2018-07-24 2022-08-02 网宿科技股份有限公司 应用程序的信息采集方法及终端
CN109376140A (zh) * 2018-08-24 2019-02-22 国网吉林省电力有限公司信息通信公司 一种静态资源自动化采集方法、系统、设备及存储介质
CN109711156B (zh) * 2018-12-28 2023-01-31 上海北信源信息技术有限公司 一种内网计算机硬盘信息监控管理的方法及系统
CN111857789A (zh) * 2019-04-29 2020-10-30 天津五八到家科技有限公司 数据处理系统
CN110275902A (zh) * 2019-06-28 2019-09-24 重庆回形针信息技术有限公司 一种数据采集分析系统及方法
CN110287471A (zh) * 2019-06-28 2019-09-27 重庆回形针信息技术有限公司 一种图表分析系统
CN110569168B (zh) * 2019-08-26 2022-07-08 腾讯科技(深圳)有限公司 一种数据交互方法、相关设备及存储介质
CN110515963A (zh) * 2019-08-30 2019-11-29 北京东软望海科技有限公司 收集统计信息的方法、装置、电子设备及可读存储介质
CN111209057B (zh) * 2020-01-10 2022-09-09 厦门瑞为信息技术有限公司 一种快速调整感知终端的方法以及装置
CN111581931B (zh) * 2020-04-26 2023-08-11 泰康保险集团股份有限公司 基于数据防泄漏系统的报表生成方法及装置
CN111694720B (zh) * 2020-06-15 2023-11-24 山东浪潮云服务信息科技有限公司 一种自动监控数据采集进度的方法
CN111897714B (zh) * 2020-06-24 2024-03-26 方欣科技有限公司 一种基于辅助测试工具的测试数据沉淀方法、装置及系统
CN112235060A (zh) * 2020-09-29 2021-01-15 石家庄市善理通益科技有限公司 一种应用于对讲终端的异常行为监控采集方法
CN114185806A (zh) * 2021-12-17 2022-03-15 平安壹钱包电子商务有限公司 软件缺陷测试方法、装置、设备及存储介质
CN118394667B (zh) * 2024-07-01 2024-09-06 浙江微特电子信息有限公司 基于人工智能的软件系统分析方法及系统

Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103188088A (zh) * 2011-12-27 2013-07-03 北京新媒传信科技有限公司 设备信息采集系统及方法
CN103248651A (zh) * 2012-02-09 2013-08-14 腾讯科技(深圳)有限公司 一种性能监控的方法和系统以及客户端和服务器
WO2014067439A1 (en) * 2012-10-29 2014-05-08 Tencent Technology (Shenzhen) Company Limited Method, system and device for monitorring data
CN104657278A (zh) * 2015-03-13 2015-05-27 百度在线网络技术(北京)有限公司 客户端性能评估方法及系统
CN105119899A (zh) * 2015-07-17 2015-12-02 世纪龙信息网络有限责任公司 非入侵式客户端运行时数据采集方法与系统
CN105373293A (zh) * 2015-12-15 2016-03-02 北京奇虎科技有限公司 一种数据采集方法和装置
CN105376335A (zh) * 2015-12-15 2016-03-02 北京奇虎科技有限公司 一种采集数据上传方法和装置
CN105391602A (zh) * 2015-12-15 2016-03-09 北京奇虎科技有限公司 一种数据采集测试方法和装置
CN105516321A (zh) * 2015-12-15 2016-04-20 北京奇虎科技有限公司 一种数据采集方法和装置
CN105515909A (zh) * 2015-12-15 2016-04-20 北京奇虎科技有限公司 一种数据采集测试方法和装置
CN105553770A (zh) * 2015-12-15 2016-05-04 北京奇虎科技有限公司 一种数据采集控制方法和装置
CN105553769A (zh) * 2015-12-15 2016-05-04 北京奇虎科技有限公司 一种数据采集分析系统和方法
CN105574150A (zh) * 2015-12-15 2016-05-11 北京奇虎科技有限公司 一种数据处理方法和装置
CN105577472A (zh) * 2015-12-15 2016-05-11 北京奇虎科技有限公司 一种数据采集测试方法和装置

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101557582B (zh) * 2008-04-08 2012-08-29 中国移动通信集团公司 一种移动通信用户信息统计方法及装置
CN102711141B (zh) * 2012-05-15 2014-12-17 上海交通大学无锡研究院 一种基于移动终端的移动网络服务质量分布式采集方法
WO2013186870A1 (ja) * 2012-06-13 2013-12-19 株式会社日立製作所 サービス監視システム、及び、サービス監視方法
CN103118095A (zh) * 2013-01-25 2013-05-22 浪潮电子信息产业股份有限公司 一种云数据中心信息差量采集方法
CN104239577A (zh) * 2014-10-09 2014-12-24 北京奇虎科技有限公司 检测网页数据真伪的方法和装置

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103188088A (zh) * 2011-12-27 2013-07-03 北京新媒传信科技有限公司 设备信息采集系统及方法
CN103248651A (zh) * 2012-02-09 2013-08-14 腾讯科技(深圳)有限公司 一种性能监控的方法和系统以及客户端和服务器
WO2014067439A1 (en) * 2012-10-29 2014-05-08 Tencent Technology (Shenzhen) Company Limited Method, system and device for monitorring data
CN104657278A (zh) * 2015-03-13 2015-05-27 百度在线网络技术(北京)有限公司 客户端性能评估方法及系统
CN105119899A (zh) * 2015-07-17 2015-12-02 世纪龙信息网络有限责任公司 非入侵式客户端运行时数据采集方法与系统
CN105373293A (zh) * 2015-12-15 2016-03-02 北京奇虎科技有限公司 一种数据采集方法和装置
CN105376335A (zh) * 2015-12-15 2016-03-02 北京奇虎科技有限公司 一种采集数据上传方法和装置
CN105391602A (zh) * 2015-12-15 2016-03-09 北京奇虎科技有限公司 一种数据采集测试方法和装置
CN105516321A (zh) * 2015-12-15 2016-04-20 北京奇虎科技有限公司 一种数据采集方法和装置
CN105515909A (zh) * 2015-12-15 2016-04-20 北京奇虎科技有限公司 一种数据采集测试方法和装置
CN105553770A (zh) * 2015-12-15 2016-05-04 北京奇虎科技有限公司 一种数据采集控制方法和装置
CN105553769A (zh) * 2015-12-15 2016-05-04 北京奇虎科技有限公司 一种数据采集分析系统和方法
CN105574150A (zh) * 2015-12-15 2016-05-11 北京奇虎科技有限公司 一种数据处理方法和装置
CN105577472A (zh) * 2015-12-15 2016-05-11 北京奇虎科技有限公司 一种数据采集测试方法和装置

Cited By (54)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109905253A (zh) * 2017-12-07 2019-06-18 航天信息股份有限公司 一种日志信息采集方法及装置
CN111198942B (zh) * 2018-10-31 2023-07-04 合肥神策数据网络科技有限公司 数据分析报告生成方法、装置、移动终端及存储介质
CN111198942A (zh) * 2018-10-31 2020-05-26 合肥神策数据网络科技有限公司 数据分析报告生成方法、装置、移动终端及存储介质
CN110159252A (zh) * 2019-06-04 2019-08-23 国网北京市电力公司 数据采集系统及方法
CN110633205A (zh) * 2019-06-20 2019-12-31 北京无限光场科技有限公司 一种埋点事件的检测方法、装置、终端设备及介质
CN112395173A (zh) * 2019-08-14 2021-02-23 腾讯科技(深圳)有限公司 信息流数据上报的方法和装置
CN112395173B (zh) * 2019-08-14 2023-10-13 腾讯科技(深圳)有限公司 信息流数据上报的方法和装置
CN112434023A (zh) * 2019-08-26 2021-03-02 长鑫存储技术有限公司 工艺数据分析方法及装置、存储介质及计算机设备
CN110995524A (zh) * 2019-10-28 2020-04-10 北京三快在线科技有限公司 流量数据监控方法、装置、电子设备和计算机可读介质
CN113126562A (zh) * 2020-01-16 2021-07-16 智能云科信息科技有限公司 数据采集方法、装置、系统及计算机可读存储介质
CN115004667B (zh) * 2020-04-24 2024-04-02 深圳市欢太科技有限公司 信息推送方法、装置、电子设备及计算机可读介质
CN115004667A (zh) * 2020-04-24 2022-09-02 深圳市欢太科技有限公司 信息推送方法、装置、电子设备及计算机可读介质
CN111611256B (zh) * 2020-04-30 2023-05-09 广东良实机电工程有限公司 设备能耗监测方法、装置、终端设备及存储介质
CN111611256A (zh) * 2020-04-30 2020-09-01 广东良实机电工程有限公司 设备能耗监测方法、装置、终端设备及存储介质
CN112181804B (zh) * 2020-08-31 2023-09-08 五八到家有限公司 一种参数校验方法、设备以及存储介质
CN112181804A (zh) * 2020-08-31 2021-01-05 五八到家有限公司 一种参数校验方法、设备以及存储介质
CN112130854A (zh) * 2020-09-09 2020-12-25 海看网络科技(山东)股份有限公司 一种iptv检测探针系统关键字的方法
CN112130854B (zh) * 2020-09-09 2023-12-22 海看网络科技(山东)股份有限公司 一种iptv检测探针系统关键字的方法
CN112015870A (zh) * 2020-09-14 2020-12-01 支付宝(杭州)信息技术有限公司 数据上传方法及装置
CN112015870B (zh) * 2020-09-14 2024-06-07 支付宝(杭州)信息技术有限公司 数据上传方法及装置
CN112328619A (zh) * 2020-09-24 2021-02-05 杭州小电科技股份有限公司 数据质量监控方法、装置、系统、电子装置和存储介质
CN113760564A (zh) * 2020-10-20 2021-12-07 北京沃东天骏信息技术有限公司 数据处理方法、装置和系统
CN114385478A (zh) * 2020-10-22 2022-04-22 腾讯科技(深圳)有限公司 一种数据采集上报方法、装置、电子设备和存储介质
CN112817782B (zh) * 2021-02-20 2023-10-13 腾讯科技(深圳)有限公司 一种数据采集上报方法、装置、电子设备和存储介质
CN112817782A (zh) * 2021-02-20 2021-05-18 腾讯科技(深圳)有限公司 一种数据采集上报方法、装置、电子设备和存储介质
CN113014647B (zh) * 2021-02-25 2022-05-03 浙江正元智慧科技股份有限公司 一种基于大数据的运维平台远程数据采集系统
CN113014647A (zh) * 2021-02-25 2021-06-22 浙江正元智慧科技股份有限公司 一种基于大数据的运维平台远程数据采集系统
CN113515507A (zh) * 2021-03-12 2021-10-19 中电建电力检修工程有限公司 应用于大坝渗水检测的方法及系统
CN113515507B (zh) * 2021-03-12 2024-02-02 中电建电力检修工程有限公司 应用于大坝渗水检测的方法及系统
CN113114736A (zh) * 2021-03-25 2021-07-13 北京数字磐石科技有限公司 矿机管理方法和系统
CN113626477A (zh) * 2021-07-19 2021-11-09 浙江浙大中控信息技术有限公司 基于水厂物联网系统的可配置报表系统及方法
CN113626477B (zh) * 2021-07-19 2023-10-10 浙江中控信息产业股份有限公司 基于水厂物联网系统的可配置报表系统及方法
CN114615291A (zh) * 2021-12-08 2022-06-10 江苏众亿国链大数据科技有限公司 一种基于物联网的数据采集方法
CN114401289B (zh) * 2021-12-31 2024-08-16 深圳市麦谷科技有限公司 任务分批上传方法及系统
CN114401289A (zh) * 2021-12-31 2022-04-26 深圳市麦谷科技有限公司 任务分批上传方法及系统
CN114460400A (zh) * 2022-01-19 2022-05-10 西北核技术研究所 一种脉冲电流注入自动化实验系统及方法
CN114296009A (zh) * 2022-03-10 2022-04-08 山东汇能电气有限公司 一种变压器运行智能分析系统
CN114296009B (zh) * 2022-03-10 2022-05-24 山东汇能电气有限公司 一种变压器运行智能分析系统
CN114785784A (zh) * 2022-04-14 2022-07-22 中国第一汽车股份有限公司 数据处理方法、装置、电子设备
CN114785784B (zh) * 2022-04-14 2023-10-24 中国第一汽车股份有限公司 数据处理方法、装置、电子设备
CN114827774A (zh) * 2022-04-26 2022-07-29 浙江正泰物联技术有限公司 一种电气数据采集方法、装置及系统
CN115102936B (zh) * 2022-06-22 2023-11-21 苏州达家迎信息技术有限公司 批量信息上传方法、装置、存储介质及电子设备
CN115102936A (zh) * 2022-06-22 2022-09-23 苏州达家迎信息技术有限公司 批量信息上传方法、装置、存储介质及电子设备
CN115378722A (zh) * 2022-08-25 2022-11-22 山东中创软件商用中间件股份有限公司 跨网络安全域的动态数据上报方法、装置、设备及介质
CN115453052A (zh) * 2022-08-31 2022-12-09 安徽天维仪表有限公司 一种用于校定气体检测仪的数据自动采集系统
CN116303689A (zh) * 2023-05-25 2023-06-23 武汉科迪智能环境股份有限公司 数据报表的生成方法、装置、计算机设备及可读存储介质
CN117215542B (zh) * 2023-11-07 2024-05-14 上海华创自动化工程股份有限公司 一种自定义数据处理系统及方法
CN117215542A (zh) * 2023-11-07 2023-12-12 上海华创自动化工程股份有限公司 一种自定义数据处理系统及方法
CN117724884A (zh) * 2023-11-20 2024-03-19 福建新大陆支付技术有限公司 一种基于数据分析的自动化测试方法
CN118627524A (zh) * 2024-07-11 2024-09-10 宁波瑞辉智能科技有限公司 基于串口屏交互连网的poe数字化采集终端及其工作方法
CN118710129A (zh) * 2024-07-11 2024-09-27 广州中车轨道交通装备有限公司 一种交通装备生产质量信息管理方法及系统
CN118474575A (zh) * 2024-07-12 2024-08-09 北京博维亚讯技术有限公司 一种集中器的数据采集分析方法及系统
CN119728817A (zh) * 2025-03-03 2025-03-28 浙江省北大信息技术高等研究院 一种终端设备数据传输方法、系统、设备和存储介质
CN121441902A (zh) * 2025-12-30 2026-01-30 天津七一二移动通信股份有限公司 一种cir自动化数据下载系统及方法

Also Published As

Publication number Publication date
CN105553769A (zh) 2016-05-04
CN105553769B (zh) 2019-03-05

Similar Documents

Publication Publication Date Title
CN105553769A (zh) 一种数据采集分析系统和方法
CN111522922B (zh) 日志信息查询方法、装置、存储介质及计算机设备
CN107391359B (zh) 一种业务测试方法及装置
CN105376335B (zh) 一种采集数据上传方法和装置
CN107391746A (zh) 日志分析方法、设备和计算机可读存储介质
CN112232881A (zh) 一种数据检测方法、装置、电子设备及存储介质
WO2017113677A1 (zh) 处理用户行为数据的方法和系统
CN108512720B (zh) 一种网站流量的统计方法及装置
CN109684052A (zh) 事务分析方法、装置、设备及存储介质
GB2569678A (en) Automation of SQL tuning method and system using statistic SQL pattern analysis
CN105373293A (zh) 一种数据采集方法和装置
US20240022507A1 (en) Information flow recognition method, network chip, and network device
CN102469117A (zh) 一种异常访问行为的识别方法及装置
CN107329894A (zh) 应用程序系统测试方法、装置及电子设备
CN111740868A (zh) 告警数据的处理方法和装置及存储介质
CN105516321A (zh) 一种数据采集方法和装置
CN115150261A (zh) 告警分析的方法、装置、电子设备及存储介质
CN105515909B (zh) 一种数据采集测试方法和装置
CN112241362B (zh) 一种测试方法、装置、服务器及存储介质
CN105553770B (zh) 一种数据采集控制方法和装置
CN105577472A (zh) 一种数据采集测试方法和装置
CN105574150A (zh) 一种数据处理方法和装置
CN107770805A (zh) 终端的标识信息的判定方法及装置
CN110011860A (zh) 基于网络流量分析的安卓应用识别方法
CN112612679A (zh) 系统运行状态监控方法、装置、计算机设备和存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16874663

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16874663

Country of ref document: EP

Kind code of ref document: A1