CN116738084A - Buried data processing method, buried data processing device, computer equipment and storage medium - Google Patents
Buried data processing method, buried data processing device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN116738084A CN116738084A CN202310392400.0A CN202310392400A CN116738084A CN 116738084 A CN116738084 A CN 116738084A CN 202310392400 A CN202310392400 A CN 202310392400A CN 116738084 A CN116738084 A CN 116738084A
- Authority
- CN
- China
- Prior art keywords
- target
- data
- buried
- acquiring
- user
- 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.)
- Pending
Links
- 238000012545 processing Methods 0.000 title claims abstract description 37
- 238000003672 processing method Methods 0.000 title claims abstract description 19
- 238000004458 analytical method Methods 0.000 claims abstract description 53
- 230000001960 triggered effect Effects 0.000 claims abstract description 13
- 238000000034 method Methods 0.000 claims description 37
- 238000013507 mapping Methods 0.000 claims description 30
- 238000010276 construction Methods 0.000 claims description 27
- 238000009933 burial Methods 0.000 claims description 10
- 238000005516 engineering process Methods 0.000 abstract description 13
- 230000008569 process Effects 0.000 description 7
- 238000007405 data analysis Methods 0.000 description 6
- 238000013473 artificial intelligence Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008520 organization Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 230000006835 compression Effects 0.000 description 2
- 238000007906 compression Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 206010044565 Tremor Diseases 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/955—Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Stored Programmes (AREA)
Abstract
The embodiment of the application belongs to the field of big data, and relates to a buried data processing method, which comprises the following steps: when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not; if yes, acquiring a target user identifier corresponding to a target user, and acquiring a target main session identifier corresponding to the target user identifier; acquiring a target initial parameter corresponding to a target main session identifier; acquiring target buried point data collected when a target page executes a target buried point event; constructing target business analysis data based on the target initial parameters and the target buried data; and constructing a target data report based on the target business analysis data. The application also provides a buried data processing device, computer equipment and a storage medium. In addition, the application also relates to a blockchain technology, and a target data report can be stored in the blockchain. The application reduces the buried point bandwidth cost and improves the generation efficiency of the target data report.
Description
Technical Field
The present application relates to the field of big data technologies, and in particular, to a method and apparatus for processing buried data, a computer device, and a storage medium.
Background
With the rapid development of mobile internet technology, various types of applications are emerging to meet user demands. In the development process of an application program, the application program is generally required to be buried so as to collect user behaviors of a user when the application program is used, so that user demand analysis is performed based on the user behaviors, and fine operation is performed according to the demands of the user.
In the prior art, when an application program is buried, the uploaded buried data carry more parameters, so that pressure is caused on a broadband and resources are wasted. And the buried point data is manually analyzed to complete the construction of the data report, so that higher labor cost is required to be consumed, the construction efficiency of the data report is low, and errors are easy to occur.
Disclosure of Invention
The embodiment of the application aims to provide a buried point data processing method, a device, computer equipment and a storage medium, which are used for solving the problems that in the prior art, when an application program is buried, the uploaded buried point data carry more parameters, so that pressure is caused on a broadband and resources are wasted. And the buried point data is manually analyzed to complete the construction of the data report, so that higher labor cost is required to be consumed, the construction efficiency of the data report is low, and the technical problem of error easily occurs.
In order to solve the above technical problems, an embodiment of the present application provides a buried data processing method, which adopts the following technical scheme:
when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not;
if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier;
acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table;
acquiring target buried point data collected when the target page executes a preset target buried point event;
constructing target business analysis data based on the target initial parameters and the target buried data;
and constructing a target data report based on the target business analysis data.
Further, before the step of acquiring the target embedded point data collected when the target page executes the preset target embedded point event, the method further includes:
acquiring buried point configuration information input by a designated user;
determining a buried point position based on the buried point configuration information;
generating a corresponding buried point code based on the buried point configuration information;
And inserting the embedded point code into the embedded point position in the target page to generate the target embedded point event.
Further, the step of constructing a target data report based on the target business analysis data specifically includes:
acquiring a preset report construction rule;
and analyzing the target business analysis data based on the report construction rule to generate the target data report corresponding to the target business analysis data.
Further, before the step of obtaining the target user identifier corresponding to the target user and obtaining the target main session identifier corresponding to the target user identifier, the method further includes:
when a user starts a target applet corresponding to the target page for the first time, acquiring a user identification corresponding to the user through a preset user information interface;
generating a main session identifier corresponding to the user identifier based on a preset cache database;
acquiring starting information corresponding to the user;
acquiring initial parameters corresponding to a preset data type from the starting information;
and dropping the initial parameter and the main session identifier into a service burial point event corresponding to the target applet, so that when the starting event of the target applet is detected, the initial parameter and the main session identifier are used as burial point data to be uploaded to a preset data interface.
Further, before the step of obtaining the target initial parameter corresponding to the target main session identifier from the preset mapping dimension table, the method further includes:
acquiring all applet starting events corresponding to the target applet;
acquiring service embedded point data corresponding to each applet starting event respectively;
and constructing the mapping dimension table based on the main session identifier and the initial parameters contained in the service embedded point data.
Further, after the step of generating the main session identifier corresponding to the user identifier based on the preset cache database, the method specifically includes:
judging whether an initial main session identifier corresponding to the user identifier is stored in the cache database;
if the initial main session identifier corresponding to the user identifier is stored, performing coverage processing on the initial main session identifier by using the main session identifier;
and if the initial main session identification corresponding to the user identification is not stored, storing the main session identification into the cache database.
Further, after the step of constructing the target data report based on the target business analysis data, the method further includes:
Acquiring a page identifier corresponding to the target page;
determining a target storage block corresponding to the page identifier from all storage blocks contained in a preset blockchain based on the page identifier;
and storing the target data report into the target storage block.
In order to solve the above technical problems, the embodiment of the present application further provides a buried data processing device, which adopts the following technical scheme:
the first judging module is used for judging whether the current environment corresponding to the target page is an applet environment or not when receiving the business operation triggered by the target user on the target page;
the first acquisition module is used for acquiring a target user identifier corresponding to the target user if yes, and acquiring a target main session identifier corresponding to the target user identifier;
the second acquisition module is used for acquiring target initial parameters corresponding to the target main session identifier from a preset mapping dimension table;
the third acquisition module is used for acquiring target buried point data collected when the target page executes a preset target buried point event;
the first construction module is used for constructing target business analysis data based on the target initial parameters and the target buried data;
And the second construction module is used for constructing a target data report based on the target business analysis data.
In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical schemes:
when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not;
if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier;
acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table;
acquiring target buried point data collected when the target page executes a preset target buried point event;
constructing target business analysis data based on the target initial parameters and the target buried data;
and constructing a target data report based on the target business analysis data.
In order to solve the above technical problems, an embodiment of the present application further provides a computer readable storage medium, which adopts the following technical schemes:
when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not;
If yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier;
acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table;
acquiring target buried point data collected when the target page executes a preset target buried point event;
constructing target business analysis data based on the target initial parameters and the target buried data;
and constructing a target data report based on the target business analysis data.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
when receiving a business operation triggered by a target user on a target page, the embodiment of the application judges whether the current environment corresponding to the target page is an applet environment or not; if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier; then, acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table; then acquiring target buried point data collected when the target page executes a preset target buried point event; constructing target business analysis data based on the target initial parameters and the target buried data; and finally, constructing a target data report based on the target business analysis data. The embodiment of the application can quickly acquire the pre-stored target initial parameters based on the target main session identification of the target user and the use of the mapping dimension table, and the target embedded point data collected when the target page executes the preset target embedded point event is acquired. In addition, the corresponding target data report is automatically and rapidly generated according to the target business analysis data constructed by the target initial parameters and the target buried data, so that the generation efficiency of the target data report is effectively improved, and the accuracy of buried data analysis is improved.
Drawings
In order to more clearly illustrate the solution of the present application, a brief description will be given below of the drawings required for the description of the embodiments of the present application, it being apparent that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without the exercise of inventive effort for a person of ordinary skill in the art.
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a method of processing buried data according to the present application;
FIG. 3 is a schematic diagram of one embodiment of a buried data processing apparatus according to the present application;
FIG. 4 is a schematic structural diagram of one embodiment of a computer device in accordance with the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
In order to make the person skilled in the art better understand the solution of the present application, the technical solution of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.
It should be noted that, the method for processing embedded data provided in the embodiment of the present application is generally executed by a server/terminal device, and accordingly, the embedded data processing apparatus is generally disposed in the server/terminal device.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow chart of one embodiment of a method of processing buried data according to the present application is shown. The buried point data processing method comprises the following steps:
Step S201, when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment.
In this embodiment, an application program in an electronic device (for example, a server/terminal device shown in fig. 1) on which the embedded data processing method is running may acquire a service operation through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection. The target page may be a h5 page specifically, and whether the current environment corresponding to the target page is an applet environment may be detected through a preset h5 module. In addition, the h5 module is a functional module with an environment detection function, which is constructed in advance.
Step S202, if yes, obtaining a target user identifier corresponding to the target user, and obtaining a target main session identifier corresponding to the target user identifier.
In this embodiment, the target user identifier specifically refers to a union id of the target user, after the target user identifier corresponding to the target user is obtained, a related interface may be called in an initialization life cycle function through the target user identifier to obtain a target main session identifier (main_session_id) corresponding to the target user identifier.
Step 203, obtaining a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table.
In this embodiment, the mapping dimension table is a pre-constructed data table storing a plurality of main session identifiers and initial parameters corresponding to the main session identifiers respectively. The above-mentioned construction process of the mapping dimension table will be described in further detail in the following embodiments, which will not be described herein.
Step S204, acquiring target embedded point data collected when the target page executes a preset target embedded point event.
In this embodiment, the target embedded point event is a built embedded point event for acquiring other important service data except the initial parameters. The initial parameters refer to general parameters, and include, for example, region information, channel information, organization information, equipment information, and traffic sources corresponding to the user. The target embedded point event is an embedded point event created from embedded point configuration information input by a data developer. The generation process of the target embedded point event will be described in further detail in the following specific embodiments, which will not be described herein.
And step S205, constructing target business analysis data based on the target initial parameters and the target buried data.
In this embodiment, the target business analysis data may be obtained by integrating the target initial parameter with the target buried data. The target business analysis data comprise the target initial parameters and the target buried point data.
And step S206, constructing a target data report based on the target business analysis data.
In this embodiment, the foregoing specific implementation process of constructing the target data report based on the target business analysis data will be described in further detail in the following specific embodiments, which will not be described herein. In addition, after the target data report is generated, analysis can be performed based on target embedded point data in the target data report, so that the active condition and the retention condition of a user are obtained, and fine granularity analysis can be performed on the user according to target initial parameters in the target data report to obtain corresponding analysis results, for example, a tremble and pull new user prefers to buy medical health products, any pull new user likes service products, and the like, so that fine operation and targeted delivery are realized.
When receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not; if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier; then, acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table; then acquiring target buried point data collected when the target page executes a preset target buried point event; constructing target business analysis data based on the target initial parameters and the target buried data; and finally, constructing a target data report based on the target business analysis data. The method and the system can quickly acquire the pre-stored target initial parameters based on the target main session identification of the target user and the use of the mapping dimension table, and acquire the target embedded point data collected when the target page executes the preset target embedded point event. In addition, the corresponding target data report is automatically and rapidly generated according to the target business analysis data constructed by the target initial parameters and the target buried data, so that the generation efficiency of the target data report is effectively improved, and the accuracy of buried data analysis is improved.
In some alternative implementations, before step S204, the electronic device may further perform the following steps:
and acquiring buried point configuration information input by a specified user.
In this embodiment, the above-described designated user may refer to a data developer. The above-mentioned buried point configuration information refers to setting information related to the buried point of the target page, and the buried point configuration information may include a buried point object and a buried point event description. For example, the embedded point configuration information may include the number of daily starts of the user for the page, the number of pages per visit, the alternate day visit, etc. The embedded point configuration information uploaded by the appointed user can be obtained through an interactive interface of the electronic equipment, and the embedded point configuration information is stored.
And determining the buried point position based on the buried point configuration information.
In this embodiment, the embedded point position is a code position corresponding to the embedded point event executed on the embedded point object in the code of the electronic device.
And generating a corresponding buried point code based on the buried point configuration information.
In the present embodiment, the buried point code is code data indicating that the buried point data on the above-described buried point object is collected.
And inserting the embedded point code into the embedded point position in the target page to generate the target embedded point event.
In this embodiment, the embedded point code is inserted into the embedded point in the page code corresponding to the target page to generate the embedded point collection event, that is, the target embedded point event, and when the embedded point code is executed, the embedded point data is collected once and reported to the server.
The embedded point configuration information input by a designated user is obtained; then determining the position of the buried point based on the buried point configuration information; then generating a corresponding buried point code based on the buried point configuration information; and inserting the embedded point code into the embedded point position in the target page to generate the target embedded point event. The application can intelligently and rapidly complete the embedded point processing of the target page based on the embedded point configuration information input by the appointed user, and generate the corresponding target embedded point event, thereby realizing the automation of the embedded point process, and being beneficial to accurately collecting the required target embedded point data by executing the target embedded point event.
In some alternative implementations of the present embodiment, step S206 includes the steps of:
and acquiring preset report construction rules.
In this embodiment, the report construction rule refers to a rule that performs data analysis on collected service analysis data, so as to generate a corresponding report. The report construction rules can be compiled and uploaded by a data developer according to actual service use requirements and matched with the buried point configuration information. Alternatively, the report construction rules may also be generic report construction rules.
And analyzing the target business analysis data based on the report construction rule to generate the target data report corresponding to the target business analysis data.
The method comprises the steps of obtaining preset report construction rules; and further analyzing the target business analysis data based on the report construction rule to generate the target data report corresponding to the target business analysis data. The application can quickly generate the target data report corresponding to the target business analysis data based on the report construction rule, thereby improving the generation efficiency of the target data report and the accuracy of buried data analysis.
In some alternative implementations, before step S202, the electronic device may further perform the following steps:
when a user starts a target applet corresponding to the target page for the first time, a user identification corresponding to the user is acquired through a preset user information interface.
In this embodiment, the user information interface refers to an interface for acquiring user basic information, and the user identifier refers to a union id. The UnionID in the user basic information interface is obtained to distinguish the UnionID of the user, but the UnionID is noted that: the public number will only acquire the UnionID after being bound to the WeChat open platform account number. The UnionID of the user is unique as long as it is a public number under the same WeChat open platform account. I.e., for the same user, the UnionID is the same for different applications under the same WeChat open platform account.
And generating a main session identifier corresponding to the user identifier based on a preset cache database.
In this embodiment, the cache database is specifically Redis. Redis full name Remote Dictionary Server (i.e., remote dictionary service), which is a memory-based key-value relational-less (NoSQL) database written by Italian Salvatore Sanfilippo in the C language.
And acquiring starting information corresponding to the user.
In this embodiment, the start information is related information corresponding to the user start target applet, and may at least include information such as a user source channel, whether the user is sharing, a user target page, and user region information.
And acquiring initial parameters corresponding to the preset data types from the starting information.
In this embodiment, the data types are preset data types corresponding to user basic information, including region information, channel information, organization information, device information, and traffic source information. Correspondingly, the initial parameters comprise region information, channel information, organization information, equipment information and flow sources corresponding to the users.
And dropping the initial parameter and the main session identifier into a service burial point event corresponding to the target applet, so that when the starting event of the target applet is detected, the initial parameter and the main session identifier are used as burial point data to be uploaded to a preset data interface.
When a user starts a target applet corresponding to the target page for the first time, a user identification corresponding to the user is obtained through a preset user information interface; then generating a main session identifier corresponding to the user identifier based on a preset cache database; acquiring starting information corresponding to the user; subsequently, initial parameters corresponding to the preset data types are obtained from the starting information; and finally, the initial parameters and the main session identifier are dropped into a service burial point event corresponding to the target applet, so that when the starting event of the target applet is detected, the initial parameters and the main session identifier are used as burial point data to be uploaded to a preset data interface. According to the method, when the user starts the target applet corresponding to the target page for the first time, the main session identification and the initial parameters of the user are intelligently collected and uploaded to the data interface for storage, and then the data interface can be queried based on the follow-up data interface, so that the required main session identification and initial parameters of the user can be quickly and accurately obtained.
In some alternative implementations, before step S203, the electronic device may further perform the following steps:
And acquiring all the applet starting events corresponding to the target applet.
In the present embodiment of the present application, in the present embodiment,
and acquiring service embedded point data corresponding to each applet starting event.
In this embodiment, when an applet starting event is detected, by executing a service embedded point event corresponding to a target applet in the target applet, the collected initial parameters and the main session identifier are uploaded as embedded point data to a preset data interface.
And constructing the mapping dimension table based on the main session identifier and the initial parameters contained in the service embedded point data.
In this embodiment, the main session identifier may be used as a main key based on a mapping relationship between the main session identifier and the initial parameter, and the initial parameter corresponding to the main session identifier may be used as a key value to be stored in a preset blank data table, so as to generate a required mapping dimension table.
The method comprises the steps of obtaining all applet starting events corresponding to the target applet; then obtaining service embedded point data corresponding to each small program starting event respectively; and constructing the mapping dimension table based on the main session identifier and the initial parameters contained in the service embedded point data. The application can quickly construct the required mapping dimension table based on the obtained main session identification and initial parameters in the service embedded point data corresponding to each small program starting event, is beneficial to quickly obtaining the specific initial parameters corresponding to the specific main session identification by inquiring the mapping dimension table, and improves the obtaining efficiency of the specific initial parameters. For a data developer, mapping acquisition of initial parameters is realized in a dimension table mode, so that flexible expansibility of parameter data is improved, and development workload of the data developer is reduced.
In some optional implementations, after the step of generating the main session identifier corresponding to the user identifier based on the preset cache database, the electronic device may further perform the following steps:
and judging whether an initial main session identifier corresponding to the user identifier is stored in the cache database.
And if the initial main session identifier corresponding to the user identifier is stored, performing coverage processing on the initial main session identifier by using the main session identifier.
In this embodiment, if a record of an initial main session identifier corresponding to the user identifier already exists in the cache database, the initial main session identifier is intelligently used to perform overlay processing on the initial main session identifier, so as to ensure the data uniqueness of each main session identifier in the database table.
And if the initial main session identification corresponding to the user identification is not stored, storing the main session identification into the cache database.
Judging whether an initial main session identifier corresponding to the user identifier is stored in the cache database or not; if the initial main session identifier corresponding to the user identifier is stored, performing coverage processing on the initial main session identifier by using the main session identifier; and if the initial main session identification corresponding to the user identification is not stored, storing the main session identification into the cache database. The application generates the main session identifier corresponding to the user identifier by using the cache database, and intelligently updates the main session identifier in the cache database so as to ensure the data uniqueness of each main session identifier in the cache database.
In some optional implementations of this embodiment, after step S206, the electronic device may further perform the following steps:
and acquiring a page identifier corresponding to the target page.
In this embodiment, the page identifier may refer to a page name of the target page.
And determining a target storage block corresponding to the page identifier from all storage blocks contained in a preset blockchain based on the page identifier.
In this embodiment, the blockchain is divided into a plurality of corresponding memory blocks that are respectively applied to storing the data report of different pages according to the page identifiers of the different pages in advance. The page identifiers of the pages have a one-to-one correspondence with the memory blocks.
And storing the target data report into the target storage block.
The method comprises the steps of obtaining a page identifier corresponding to the target page; then, determining a target storage block corresponding to the page identifier from all storage blocks contained in a preset blockchain based on the page identifier; and further storing the target data report into the target storage block. According to the application, the target data report is stored by using the target storage block corresponding to the page identifier of the target page in the block chain, so that the storage intelligence and the storage normalization of the data report are improved, and the required data report can be quickly and accurately searched from the storage block.
It should be emphasized that, to further ensure the privacy and security of the target data report, the target data report may also be stored in a node of a blockchain.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
With further reference to fig. 3, as an implementation of the method shown in fig. 2 described above, the present application provides an embodiment of a buried data processing apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which is particularly applicable to various electronic devices.
As shown in fig. 3, the buried data processing apparatus 300 according to the present embodiment includes: a first judging module 301, a first acquiring module 302, a second acquiring module 303, a third acquiring module 304, a first constructing module 305 and a second constructing module 306. Wherein:
the first judging module 301 is configured to judge, when a service operation triggered by a target user on a target page is received, whether a current environment corresponding to the target page is an applet environment;
a first obtaining module 302, configured to obtain, if yes, a target user identifier corresponding to the target user, and obtain a target main session identifier corresponding to the target user identifier;
a second obtaining module 303, configured to obtain, from a preset mapping dimension table, a target initial parameter corresponding to the target main session identifier;
a third obtaining module 304, configured to obtain target embedded points collected when the target page executes a preset target embedded point event;
A first construction module 305, configured to construct target business analysis data based on the target initial parameter and the target buried data;
a second construction module 306, configured to construct a target data report based on the target business analysis data.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the buried data processing apparatus further includes:
the fourth acquisition module is used for acquiring buried point configuration information input by a specified user;
the first determining module is used for determining the position of the buried point based on the buried point configuration information;
the first generation module is used for generating corresponding buried point codes based on the buried point configuration information;
and the second generation module is used for inserting the embedded point code into the embedded point position in the target page to generate the target embedded point event.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some alternative implementations of the present embodiment, the second building module 306 includes:
The acquisition sub-module is used for acquiring preset report construction rules;
and the generation sub-module is used for analyzing the target business analysis data based on the report construction rule and generating the target data report corresponding to the target business analysis data.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the buried data processing apparatus further includes:
a fifth acquisition module, configured to acquire, through a preset user information interface, a user identifier corresponding to the user when the user starts a target applet corresponding to the target page for the first time;
the third generation module is used for generating a main session identifier corresponding to the user identifier based on a preset cache database;
a sixth acquisition module, configured to acquire start information corresponding to the user;
a seventh obtaining module, configured to obtain an initial parameter corresponding to a preset data type from the start information;
and the first processing module is used for dropping the initial parameter and the main session identifier into a service burial point event corresponding to the target applet so as to upload the initial parameter and the main session identifier to a preset data interface as burial point data when a starting event of the target applet is detected.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the buried data processing apparatus further includes:
an eighth acquisition module, configured to acquire all applet starting events corresponding to the target applet;
a ninth acquisition module, configured to acquire service embedded point data corresponding to each applet starting event respectively;
and the third construction module is used for constructing the mapping dimension table based on the main session identifier and the initial parameters contained in the business embedded point data.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the buried data processing apparatus further includes:
the second judging module is used for judging whether the initial main session identifier corresponding to the user identifier is stored in the cache database;
the second processing module is used for performing coverage processing on the initial main session identifier by using the main session identifier if the initial main session identifier corresponding to the user identifier is stored;
And the first storage module is used for storing the primary session identifier into the cache database if the initial primary session identifier corresponding to the user identifier is not stored.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the buried data processing apparatus further includes:
a tenth acquisition module, configured to acquire a page identifier corresponding to the target page;
the second determining module is used for determining a target storage block corresponding to the page identifier from all storage blocks contained in a preset block chain based on the page identifier;
and the second storage module is used for storing the target data report into the target storage block.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the buried data processing method in the foregoing embodiment one by one, which is not described herein again.
In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 4, fig. 4 is a basic structural block diagram of a computer device according to the present embodiment.
The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It should be noted that only computer device 4 having components 41-43 is shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.
The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The memory 41 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 4. Of course, the memory 41 may also comprise both an internal memory unit of the computer device 4 and an external memory device. In this embodiment, the memory 41 is typically used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of a buried data processing method, and the like. Further, the memory 41 may be used to temporarily store various types of data that have been output or are to be output.
The processor 42 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the buried data processing method.
The network interface 43 may comprise a wireless network interface or a wired network interface, which network interface 43 is typically used for establishing a communication connection between the computer device 4 and other electronic devices.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
in the embodiment of the application, when receiving the business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not; if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier; then, acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table; then acquiring target buried point data collected when the target page executes a preset target buried point event; constructing target business analysis data based on the target initial parameters and the target buried data; and finally, constructing a target data report based on the target business analysis data. The embodiment of the application can quickly acquire the pre-stored target initial parameters based on the target main session identification of the target user and the use of the mapping dimension table, and the target embedded point data collected when the target page executes the preset target embedded point event is acquired. In addition, the corresponding target data report is automatically and rapidly generated according to the target business analysis data constructed by the target initial parameters and the target buried data, so that the generation efficiency of the target data report is effectively improved, and the accuracy of buried data analysis is improved.
The present application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of a buried data processing method as described above.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
in the embodiment of the application, when receiving the business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not; if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier; then, acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table; then acquiring target buried point data collected when the target page executes a preset target buried point event; constructing target business analysis data based on the target initial parameters and the target buried data; and finally, constructing a target data report based on the target business analysis data. The embodiment of the application can quickly acquire the pre-stored target initial parameters based on the target main session identification of the target user and the use of the mapping dimension table, and the target embedded point data collected when the target page executes the preset target embedded point event is acquired. In addition, the corresponding target data report is automatically and rapidly generated according to the target business analysis data constructed by the target initial parameters and the target buried data, so that the generation efficiency of the target data report is effectively improved, and the accuracy of buried data analysis is improved.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
It is apparent that the above-described embodiments are only some embodiments of the present application, but not all embodiments, and the preferred embodiments of the present application are shown in the drawings, which do not limit the scope of the patent claims. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a thorough and complete understanding of the present disclosure. Although the application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing description, or equivalents may be substituted for elements thereof. All equivalent structures made by the content of the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the scope of the application.
Claims (10)
1. A method for processing buried data, comprising the steps of:
when receiving a business operation triggered by a target user on a target page, judging whether the current environment corresponding to the target page is an applet environment or not;
if yes, acquiring a target user identifier corresponding to the target user, and acquiring a target main session identifier corresponding to the target user identifier;
acquiring a target initial parameter corresponding to the target main session identifier from a preset mapping dimension table;
acquiring target buried point data collected when the target page executes a preset target buried point event;
constructing target business analysis data based on the target initial parameters and the target buried data;
and constructing a target data report based on the target business analysis data.
2. The method according to claim 1, further comprising, before the step of acquiring target buried data collected when the target page performs a preset target buried event:
acquiring buried point configuration information input by a designated user;
determining a buried point position based on the buried point configuration information;
generating a corresponding buried point code based on the buried point configuration information;
And inserting the embedded point code into the embedded point position in the target page to generate the target embedded point event.
3. The method for processing buried data according to claim 1, wherein said step of constructing a target data report based on said target business analysis data specifically comprises:
acquiring a preset report construction rule;
and analyzing the target business analysis data based on the report construction rule to generate the target data report corresponding to the target business analysis data.
4. The method for processing buried data according to claim 1, further comprising, before said step of acquiring a target user identifier corresponding to said target user and acquiring a target main session identifier corresponding to said target user identifier:
when a user starts a target applet corresponding to the target page for the first time, acquiring a user identification corresponding to the user through a preset user information interface;
generating a main session identifier corresponding to the user identifier based on a preset cache database;
acquiring starting information corresponding to the user;
acquiring initial parameters corresponding to a preset data type from the starting information;
And dropping the initial parameter and the main session identifier into a service burial point event corresponding to the target applet, so that when the starting event of the target applet is detected, the initial parameter and the main session identifier are used as burial point data to be uploaded to a preset data interface.
5. The method for processing buried data according to claim 4, further comprising, before said step of obtaining a target initial parameter corresponding to said target primary session identifier from a preset mapping dimension table:
acquiring all applet starting events corresponding to the target applet;
acquiring service embedded point data corresponding to each applet starting event respectively;
and constructing the mapping dimension table based on the main session identifier and the initial parameters contained in the service embedded point data.
6. The method for processing embedded data according to claim 4, wherein after the step of generating the main session identifier corresponding to the user identifier based on the preset cache database, the method specifically comprises:
judging whether an initial main session identifier corresponding to the user identifier is stored in the cache database;
if the initial main session identifier corresponding to the user identifier is stored, performing coverage processing on the initial main session identifier by using the main session identifier;
And if the initial main session identification corresponding to the user identification is not stored, storing the main session identification into the cache database.
7. The method of claim 1, further comprising, after the step of constructing a target data report based on the target business analysis data:
acquiring a page identifier corresponding to the target page;
determining a target storage block corresponding to the page identifier from all storage blocks contained in a preset blockchain based on the page identifier;
and storing the target data report into the target storage block.
8. A buried data processing apparatus, comprising:
the first judging module is used for judging whether the current environment corresponding to the target page is an applet environment or not when receiving the business operation triggered by the target user on the target page;
the first acquisition module is used for acquiring a target user identifier corresponding to the target user if yes, and acquiring a target main session identifier corresponding to the target user identifier;
the second acquisition module is used for acquiring target initial parameters corresponding to the target main session identifier from a preset mapping dimension table;
The third acquisition module is used for acquiring target buried point data collected when the target page executes a preset target buried point event;
the first construction module is used for constructing target business analysis data based on the target initial parameters and the target buried data;
and the second construction module is used for constructing a target data report based on the target business analysis data.
9. A computer device comprising a memory having stored therein computer readable instructions which when executed implement the steps of the buried data processing method according to any of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer readable instructions which when executed by a processor implement the steps of the buried data processing method according to any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310392400.0A CN116738084A (en) | 2023-04-12 | 2023-04-12 | Buried data processing method, buried data processing device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310392400.0A CN116738084A (en) | 2023-04-12 | 2023-04-12 | Buried data processing method, buried data processing device, computer equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116738084A true CN116738084A (en) | 2023-09-12 |
Family
ID=87917622
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310392400.0A Pending CN116738084A (en) | 2023-04-12 | 2023-04-12 | Buried data processing method, buried data processing device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116738084A (en) |
-
2023
- 2023-04-12 CN CN202310392400.0A patent/CN116738084A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112860662B (en) | Automatic production data blood relationship establishment method, device, computer equipment and storage medium | |
| CN115712422A (en) | Form page generation method and device, computer equipment and storage medium | |
| CN116453125A (en) | Data input method, device, equipment and storage medium based on artificial intelligence | |
| CN117873486A (en) | Front-end and back-end code automatic generation method, device, equipment and storage medium | |
| CN116956326A (en) | Authority data processing method and device, computer equipment and storage medium | |
| CN117234505A (en) | Interactive page generation method, device, equipment and storage medium thereof | |
| CN117094729A (en) | Request processing method, device, computer equipment and storage medium | |
| CN117057935A (en) | Data processing method, device, equipment and storage medium based on field design | |
| CN116796840A (en) | Medical entity information extraction method, device, computer equipment and storage medium | |
| CN116821493A (en) | Message pushing method, device, computer equipment and storage medium | |
| CN116383787A (en) | Page creation method, page creation device, computer equipment and storage medium | |
| CN116450723A (en) | Data extraction method, device, computer equipment and storage medium | |
| CN116738084A (en) | Buried data processing method, buried data processing device, computer equipment and storage medium | |
| CN116795882A (en) | Data acquisition method, device, computer equipment and storage medium | |
| CN116820443A (en) | Data analysis method, device, computer equipment and storage medium | |
| CN118212074A (en) | Data recommendation method, device, computer equipment and storage medium | |
| CN117076775A (en) | Information data processing method, information data processing device, computer equipment and storage medium | |
| CN117217684A (en) | Index data processing method and device, computer equipment and storage medium | |
| CN117421233A (en) | Annotation-based code generation method, annotation-based code generation device, computer equipment and storage medium | |
| CN117422523A (en) | Product online method and device, computer equipment and storage medium | |
| CN116910095A (en) | Buried point processing method, buried point processing device, computer equipment and storage medium | |
| CN118197626A (en) | Information generation method, device, equipment and storage medium based on artificial intelligence | |
| CN115826973A (en) | List page generation method and device, computer equipment and storage medium | |
| CN117034173A (en) | Data processing method, device, computer equipment and storage medium | |
| CN117421207A (en) | Intelligent evaluation influence point test method, intelligent evaluation influence point test device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |